JP2024076741A - Work machine, information processor, and program - Google Patents

Abstract

To provide a technique capable of appropriately grasping the shape of a work object of a work machine.SOLUTION: A shovel 100 includes a controller 30 for estimating the shape of a work object according to operation of the shovel 100, and sensors S1 to S6 for acquiring data relating on the track of a work part (bucket 6) of the shovel 100, wherein the controller 30 estimates the shape of the work object, on the basis of the data relating on the track of the bucket 6 at the time of execution of excavation operation.SELECTED DRAWING: Figure 8

Description

This disclosure relates to work machines, etc.

Conventionally, there are known work machines such as excavators that are operated by an operator or that operate autonomously (see Patent Document 1).

JP 2021-188432 A

However, for example, an operator riding on a shovel may have a blind spot for part of the ground to be worked on due to unevenness in the soil and sand, shovel attachments, etc. Furthermore, when a shovel is remotely operated, the operator must operate it while looking at images from a camera mounted on the shovel, and depending on the state of the camera image, it may be difficult to grasp the shape of the ground to be worked on. For this reason, the shape of the work target is recognized based on data from a camera, a ranging sensor (distance sensor), etc., and the shape of the work target may be displayed on a display mounted in the cabin of the work machine or a display for remote operation.

For example, when an excavator is operated autonomously, the trajectory of the working part of the shovel (bucket) may be determined according to the shape of the soil on the ground where the work is to be carried out. In this case, the shape of the work object is recognized based on data from a camera, distance measurement sensor, etc., and the trajectory of the working part of the work machine is determined based on the shape of the work object.

However, when using a camera or distance measurement sensor mounted on an excavator, there is a possibility that occlusion will occur, where the shape of part of the work object cannot be measured because it is blocked by the excavator attachment or unevenness in the soil. This may result in, for example, a hole appearing in part of the shape of the work object displayed on the display, creating an unfavorable situation in terms of supporting the operator's operation. In addition, for example, because part of the shape of the work object cannot be measured, there is a possibility that the accuracy of generating the trajectory of the work part for autonomous driving will deteriorate.

In view of the above problems, the objective is to provide a technology that can more appropriately grasp the shape of the work target of a work machine.

In order to achieve the above object, in one embodiment of the present disclosure,
A processing device is provided for estimating the shape of a work target in accordance with the operation of the work machine.
A work machine is provided.

In another embodiment of the present disclosure,
A shape of a work target of the work machine is estimated in accordance with the operation of the work machine.
An information processing device is provided.

In still another embodiment of the present disclosure,
In the information processing device,
A shape of a work target of the work machine is estimated in accordance with the operation of the work machine.
The program is provided.

In still another embodiment of the present disclosure,
Support equipment:
A shape of a work target of the work machine is estimated in accordance with the operation of the work machine;
Displaying the estimated result of the shape of the work object;
The program is provided.

According to the above-described embodiment, it is possible to more appropriately grasp the shape of the work target of the work machine.

FIG. 1 illustrates an example of an operation support system. FIG. 2 is a top view showing an example of a shovel. FIG. 2 is a diagram illustrating an example of a configuration for remote control of a shovel. FIG. 2 is a diagram illustrating an example of a hardware configuration of a shovel. FIG. 2 illustrates an example of a hardware configuration of an information processing device. FIG. 2 is a functional block diagram showing a first example of a functional configuration of the operation support system. FIG. 11 is a functional block diagram showing a second example of the functional configuration of the operation support system. 11 is a flowchart illustrating an example of a process performed by a work object shape acquisition unit. FIG. 2 is a diagram illustrating an example of an observation target area. FIG. 13 is a diagram illustrating an example of an affected area.

The following describes the embodiment with reference to the drawings.

[Overview of the operation support system]
An overview of an operation support system SYS according to this embodiment will be described with reference to FIGS. 1 to 3. FIG.

Figure 1 is a diagram showing an example of an operation support system SYS. In Figure 1, a left side view of a shovel 100 is shown. Figure 2 is a top view showing an example of the shovel 100. Figure 3 is a diagram showing an example of a configuration related to remote operation of the shovel 100. Below, the direction in which the attachment AT extends when viewed from above the shovel 100 (the upward direction in Figure 2) is defined as "front," and directions on the shovel 100 or directions seen from the shovel 100 may be described.

As shown in FIG. 1, the operation support system SYS includes an excavator 100, an information processing device 200, and a sensor group 300.

The operation support system SYS uses the information processing device 200 to cooperate with the shovel 100 and provide support regarding the operation of the shovel 100.

The operation support system SYS may include one or more excavators 100.

The excavator 100 is a work machine that receives operation support in the operation support system SYS.

As shown in Figures 1 and 2, the excavator 100 includes a lower traveling body 1, an upper rotating body 3, an attachment AT including a boom 4, an arm 5, and a bucket 6, and a cabin 10.

The lower traveling body 1 uses crawlers 1C to travel the excavator 100. The crawlers 1C include a left crawler 1CL and a right crawler 1CR. The crawler 1CL is hydraulically driven by a traveling hydraulic motor 1ML. Similarly, the crawler 1CL is hydraulically driven by a traveling hydraulic motor 1MR. This allows the lower traveling body 1 to travel on its own.

The upper rotating body 3 is mounted on the lower traveling body 1 so as to be rotatable (freely rotatable) via the rotating mechanism 2. For example, the upper rotating body 3 rotates relative to the lower traveling body 1 when the rotating mechanism 2 is hydraulically driven by a rotating hydraulic motor 2M.

The boom 4 is attached to the front center of the upper rotating body 3 so that it can be raised and lowered around a rotation axis that runs along the left-right direction. The arm 5 is attached to the tip of the boom 4 so that it can rotate around a rotation axis that runs along the left-right direction. The bucket 6 is attached to the tip of the arm 5 so that it can rotate around a rotation axis that runs along the left-right direction.

The bucket 6 is an example of an end attachment and is used, for example, for excavation work, slope work, and ground leveling work.

The bucket 6 is attached to the tip of the arm 5 in a manner that allows it to be appropriately replaced depending on the work content of the excavator 100. In other words, instead of the bucket 6, a bucket of a different type from the bucket 6, such as a relatively large bucket, a bucket for slopes, or a dredging bucket, may be attached to the tip of the arm 5. In addition, an end attachment of a type other than a bucket, such as an agitator, breaker, or crusher, may be attached to the tip of the arm 5. In addition, a spare attachment such as a quick coupling or tilt rotator may be provided between the arm 5 and the end attachment.

The boom 4, arm 5, and bucket 6 are hydraulically driven by a boom cylinder 7, arm cylinder 8, and bucket cylinder 9, respectively.

The cabin 10 is a control room where an operator sits and operates the excavator 100. The cabin 10 is mounted, for example, on the front left side of the upper rotating body 3.

The excavator 100 is equipped with a communication device 60 and can communicate with the information processing device 200 via a specified communication line NW.

The communication line NW may include, for example, a local network (LAN: Local Area Network) at a work site. The communication line NW may also include a wide area network (WAN: Wide Area Network). Wide area networks include, for example, mobile communication networks ending in base stations, satellite communication networks using communication satellites, and the Internet network. The communication line NW may also include, for example, short-distance communication lines based on wireless communication standards such as WiFi and Bluetooth (registered trademark).

For example, the excavator 100 operates driven elements such as the lower traveling body 1 (i.e., a pair of left and right crawlers 1CL, 1CR), upper rotating body 3, boom 4, arm 5, and bucket 6 in response to the operation of an operator in the cabin 10.

In addition, instead of or in addition to being configured to be operable by an operator inside the cabin 10, the shovel 100 may be configured to be remotely operable from outside the shovel 100. When the shovel 100 is remotely operated, the interior of the cabin 10 may be unmanned. When the shovel 100 is dedicated to remote operation, the cabin 10 may be omitted. In the following description, it is assumed that the operation of the operator includes at least one of the operation of the operating device 26 by the operator inside the cabin 10 and the remote operation by an external operator.

For example, as shown in FIG. 3, remote operation includes a mode in which the shovel 100 is operated by operation input related to the actuator of the shovel 100 performed by a remote operation support device 400 capable of communicating with the shovel 100 via a communication line NW. The remote operation support device 400 may be provided separately from the information processing device 200, or may be the information processing device 200.

The remote operation support device 400 is provided, for example, in a management center that manages the work of the shovel 100 from the outside. The remote operation support device 400 may also be a portable operation terminal, in which case the operator can remotely operate the shovel 100 while directly checking the work status of the shovel 100 from the vicinity of the shovel 100.

The shovel 100 may transmit, for example, an image (hereinafter, "peripheral image") representing the surroundings including the front of the shovel 100 based on an image captured by an imaging device mounted on the shovel 100 to the remote operation support device 400 through the communication device 60 described later. The shovel 100 may also transmit an image captured by the imaging device to the remote operation support device 400 through the communication device 60, and the remote operation support device 400 may process the captured image received from the shovel 100 to generate a peripheral image. The remote operation support device 400 may then display a peripheral image representing the surroundings including the front of the shovel 100 on its own display device. Various information images (information screens) displayed on the output device 50 (display device 50A) inside the cabin 10 of the shovel 100 may also be displayed on the display device of the remote operation support device 400. This allows an operator using the remote operation support device 400 to remotely operate the shovel 100 while checking the display contents of, for example, an image representing the surroundings of the shovel 100 and an information screen displayed on the display device. The excavator 100 may operate actuators and drive driven elements such as the lower traveling body 1, the upper rotating body 3, the boom 4, the arm 5, and the bucket 6 in response to a remote operation signal indicating the content of the remote operation received from the remote operation support device 400 by the communication device 60.

Remote operation may also include a mode in which the shovel 100 is operated by external voice input or gesture input to the shovel 100 by a person (e.g., a worker) around the shovel 100. Specifically, the shovel 100 recognizes voices uttered by surrounding workers and gestures made by workers through a voice input device (e.g., a microphone) or a gesture input device (e.g., an imaging device) mounted on the shovel 100. The shovel 100 may then operate actuators according to the contents of the recognized voices and gestures to drive driven elements such as the lower traveling body 1 (left and right crawlers 1C), upper rotating body 3, boom 4, arm 5, and bucket 6.

The excavator 100 may also automatically operate the actuators regardless of the content of the operator's operation. This allows the excavator 100 to realize a function for automatically operating at least some of the driven elements such as the lower traveling body 1, the upper rotating body 3, and the attachment AT, i.e., a so-called "automatic driving function" or "machine control (MC) function."

The automatic driving function includes, for example, a semi-automatic driving function (operation assistance type MC function). The semi-automatic driving function is a function that automatically operates a driven element (actuator) other than the driven element (actuator) to be operated in response to the operation of the operator. The automatic driving function may also include a fully automatic driving function (fully automatic MC function). The fully automatic driving function is a function that automatically operates at least a part of a plurality of driven elements (hydraulic actuators) on the premise that there is no operation of the operator. In the shovel 100, when the fully automatic driving function is enabled, the inside of the cabin 10 may be unmanned. In addition, when the shovel 100 is dedicated to fully automatic operation, the cabin 10 may be omitted. In addition, the semi-automatic driving function and the fully automatic driving function include, for example, a rule-based automatic driving function. The rule-based automatic driving function is an automatic driving function in which the operation content of the driven element (actuator) to be the target of automatic operation is automatically determined according to a rule that is specified in advance. In addition, the semi-automatic driving function and the fully automatic driving function may include an autonomous driving function. The autonomous driving function is a function in which the excavator 100 autonomously makes various decisions and determines the operation of the driven element (hydraulic actuator) that is the target of the autonomous driving based on the results of those decisions.

The work of the shovel 100 may also be remotely monitored. In this case, a remote monitoring support device having the same functions as the remote operation support device 400 may be provided. The remote monitoring support device is, for example, the information processing device 200. This allows a monitor, who is a user of the remote monitoring support device, to monitor the status of the work of the shovel 100 while checking the surrounding image displayed on the display device of the remote monitoring support device. Also, for example, if the monitor determines it is necessary from the viewpoint of safety, the monitor can use the input device of the remote monitoring support device to make a specified input, thereby intervening in the operation by the operator of the shovel 100 or automatic operation and bringing the shovel 100 to an emergency stop.

The information processing device 200 communicates with the shovel 100 to cooperate with it and provide support for the operation of the shovel 100.

The information processing device 200 is, for example, a server device or a management terminal device installed in a management office in the work site of the shovel 100, or in a management center that manages the operating status of the shovel 100, which is located in a place different from the work site of the shovel 100. The server device may be an on-premise server, a cloud server, or an edge server. The management terminal device may be, for example, a stationary terminal device such as a desktop PC (Personal Computer), or a portable terminal device (mobile terminal) such as a tablet terminal, a smartphone, or a laptop PC. In the latter case, a worker at the work site, a supervisor who supervises the work, a manager who manages the work site, etc. can move around the work site carrying the portable information processing device 200. In the latter case, an operator can, for example, bring the portable information processing device 200 into the cabin of the shovel 100.

The information processing device 200, for example, acquires data on the operating state from the shovel 100. This enables the information processing device 200 to grasp the operating state of the shovel 100 and monitor the presence or absence of abnormalities in the shovel 100. The information processing device 200 can also display data on the operating state of the shovel 100 via, for example, a display device 208 described below, and allow a user to confirm the data. The information processing device 200 can also, for example, train a learning model to learn the operating state of the shovel 100, and generate a trained model for supporting the operation of the shovel 100.

The information processing device 200 may also transmit to the shovel 100 various data such as programs and reference data used in the processing of the controller 30, etc., to the shovel 100. This allows the shovel 100 to perform various processes related to the operation of the shovel 100 using the various data downloaded from the information processing device 200.

The sensor group 300 is installed at the work site of the shovel 100. The work target is, for example, soil and sand in the work area around the shovel 100.

For example, if the operation support system SYS includes multiple shovels 100, a sensor group 300 is provided for each shovel 100. Also, if multiple shovels 100 included in the operation support system SYS work at the same work site, one sensor group 300 may be shared by the multiple shovels 100.

The sensor group 300 includes sensors 300-1 to 300-M (M: an integer of 2 or more). The sensors 300-1 to 300-M measure the state of objects at the work site around the shovel 100 and acquire measurement data relating to the state. Objects at the work site include the work target around the shovel 100 (soil and sand in the work area), as well as other shovels around the shovel 100, work machines such as bulldozers, and work vehicles such as trucks for transporting soil and sand. The state of an object includes the shape and characteristics of the object.

The sensors 300-1 to 300-M include, for example, a distance measurement sensor (distance sensor). The distance measurement sensor includes, for example, a LIDAR (Light Detecting and Ranging), a millimeter wave radar, an ultrasonic sensor, an infrared sensor, and the like. The sensors 300-1 to 300-M may also include, for example, a stereo camera, a TOF (Time Of Flight) camera, and other 3D cameras capable of acquiring data related to distance (depth) in addition to two-dimensional images. The sensors 300-1 to 300-M may also include a mixture of distance measurement sensors and 3D cameras. This allows the sensor group 300 to acquire measurement data representing the shape of objects at the work site around the shovel 100. Hereinafter, sensors capable of acquiring measurement data representing the shape of objects, such as distance measurement sensors and 3D cameras, may be referred to as "shape sensors" for convenience.

The sensors 300-1 to 300-M may also include a multi-wavelength spectroscopic camera. The multi-wavelength spectroscopic camera includes, for example, a multispectral camera and a hyperspectral camera. This allows the sensor group 300 to acquire measurement data that represents the characteristics of objects at the work site around the shovel 100, such as the hardness and moisture content of soil and sand. Hereinafter, for the sake of convenience, a sensor that can acquire measurement data that represents the characteristics of an object, such as a multi-wavelength spectroscopic camera, may be referred to as a "characteristic sensor."

For example, sensors 300-1 to 300-M include multiple shape sensors. The multiple shape sensors may be provided in different locations on the work site around the shovel 100, and such that the sensing range of each sensor overlaps with the sensing range of at least one other shape sensor. As a result, even if occlusion occurs in the measurement data of one shape sensor and measurement data representing the shape of an object in a portion of the sensing range cannot be obtained, the other shape sensors may be able to obtain measurement data representing the shape of the object in that range. Therefore, the sensor group 300 can more reliably obtain measurement data representing the shape of objects in the work site around the shovel 100.

The sensors 300-1 to 300-M may also include multiple characteristic sensors. The multiple characteristic sensors may be provided in different locations in the work site around the shovel 100, and so that the sensing range of each sensor overlaps with at least one other characteristic sensor. As a result, even if occlusion occurs in the measurement data of one characteristic sensor and measurement data representing the characteristics of an object in a portion of the sensing range cannot be obtained, the other shape sensors may be able to obtain measurement data representing the characteristics of the object in that range. Therefore, the sensor group 300 can more reliably obtain measurement data representing the characteristics of objects in the work site around the shovel 100.

The sensors 300-1 to 300-M may also include a sensor having both the functions of a shape sensor and a characteristic sensor (hereinafter, an "integrated sensor"). In this case, the sensors 300-1 to 300-M may include multiple integrated sensors. The multiple characteristic sensors may be provided at different locations in the work site around the shovel 100, and each of the sensing ranges may overlap with at least one other characteristic sensor.

The sensor group 300 may simply include only one shape sensor or one characteristic sensor. Furthermore, instead of the sensor group 300, the operation support system SYS may simply include only one sensor capable of acquiring measurement data regarding the state of objects at the work site around the shovel 100.

Sensors 300-1 to 300-M may be fixed to the work site around shovel 100, or may be mounted on a mobile object capable of moving within the work site around shovel 100. Mobile objects include, for example, work machines and work vehicles that move within the work site. Mobile objects that can move within the work site may also include, for example, flying objects such as drones that fly above the work site.

The output (measurement data) of the sensors 300-1 to 300-M is taken into the information processing device 200 through the communication line NW. The output of the sensors 300-1 to 300-M is taken into the information processing device 200 directly through the communication line NW, for example. The output of the sensors 300-1 to 300-M may also be taken into the shovel 100 once through the communication line NW, and then taken into the information processing device 200 via the shovel 100. If the sensors 300-1 to 300-M are mounted on a specific device, such as the above-mentioned mobile object, the output of the sensors 300-1 to 300-M may also be taken into the specific device once, and then taken into the information processing device 200 from that device.

[Hardware configuration of operation support system]
Next, the hardware configuration of the operation support system SYS will be described with reference to FIGS. 4 and 5 in addition to FIGS. 1 to 3.

The hardware configuration of the remote operation support device 400 may be the same as that of the information processing device 200. Therefore, illustrations and descriptions of the hardware configuration of the remote operation support device 400 will be omitted.

<Excavator hardware configuration>
FIG. 4 is a block diagram showing an example of a hardware configuration of the shovel 100.

In Figure 4, the paths through which mechanical power is transmitted are indicated by double lines, the paths through which high-pressure hydraulic oil that drives the hydraulic actuator flows are indicated by solid lines, the paths through which pilot pressure is transmitted are indicated by dashed lines, and the paths through which electrical signals are transmitted are indicated by dotted lines.

The excavator 100 includes various components, such as a hydraulic drive system for hydraulically driving the driven elements, an operation system for operating the driven elements, a user interface system for exchanging information with the user, a communication system for communicating with the outside world, and a control system for various controls.

<Hydraulic drive system>
4 , the hydraulic drive system of the excavator 100 includes hydraulic actuators HA that hydraulically drive each of the driven elements, such as the lower traveling structure 1 (left and right crawlers 1C), upper rotating structure 3, boom 4, arm 5, and bucket 6, as described above. The hydraulic drive system of the excavator 100 according to this embodiment also includes an engine 11, a regulator 13, a main pump 14, and a control valve 17.

The hydraulic actuator HA includes travel hydraulic motors 1ML, 1MR, swing hydraulic motor 2M, boom cylinder 7, arm cylinder 8, and bucket cylinder 9.

In addition, in the shovel 100, some or all of the hydraulic actuators HA may be replaced with electric actuators. In other words, the shovel 100 may be a hybrid shovel or an electric shovel.

The engine 11 is the prime mover of the excavator 100 and the main power source in the hydraulic drive system. The engine 11 is, for example, a diesel engine that uses light oil as fuel. The engine 11 is mounted, for example, at the rear of the upper rotating body 3. The engine 11 rotates at a constant speed at a preset target speed under direct or indirect control by the controller 30 (described later), for example, and drives the main pump 14 and the pilot pump 15.

In addition, other prime movers (e.g., electric motors) may be installed in the excavator 100 instead of or in addition to the engine 11.

The regulator 13 controls (adjusts) the discharge volume of the main pump 14 under the control of the controller 30. For example, the regulator 13 adjusts the angle of the swash plate of the main pump 14 (hereinafter, the "tilt angle") in response to a control command from the controller 30.

The main pump 14 supplies hydraulic oil to the control valve 17 through a high-pressure hydraulic line. The main pump 14 is mounted, for example, at the rear of the upper rotating body 3, similar to the engine 11. As described above, the main pump 14 is driven by the engine 11. The main pump 14 is, for example, a variable displacement hydraulic pump, and as described above, under the control of the controller 30, the tilt angle of the swash plate is adjusted by the regulator 13 to adjust the stroke length of the piston, thereby controlling the discharge flow rate and discharge pressure.

The control valve 17 drives the hydraulic actuators HA in response to the operator's operation of the operating device 26, the contents of remote operation, or operation commands corresponding to the automatic operation function. The control valve 17 is mounted, for example, in the center of the upper rotating body 3. As described above, the control valve 17 is connected to the main pump 14 via a high-pressure hydraulic line, and selectively supplies hydraulic oil supplied from the main pump 14 to each hydraulic actuator in response to the operator's operation or operation commands corresponding to the automatic operation function. Specifically, the control valve 17 includes multiple control valves (directional control valves) that control the flow rate and flow direction of the hydraulic oil supplied from the main pump 14 to each hydraulic actuator HA.

<Controls>
As shown in FIG. 4 , the operating system of the excavator 100 includes a pilot pump 15 , an operating device 26 , a hydraulic control valve 31 , a shuttle valve 32 , and a hydraulic control valve 33 .

The pilot pump 15 supplies pilot pressure to various hydraulic equipment via a pilot line 25. The pilot pump 15 is mounted, for example, at the rear of the upper rotating body 3, similar to the engine 11. The pilot pump 15 is, for example, a fixed displacement hydraulic pump, and is driven by the engine 11 as described above.

The pilot pump 15 may be omitted. In this case, the relatively high pressure hydraulic oil discharged from the main pump 14 is reduced in pressure by a specified pressure reducing valve, and the relatively low pressure hydraulic oil is supplied to various hydraulic equipment as pilot pressure.

The operating device 26 is provided near the cockpit of the cabin 10, and is used by the operator to operate the various driven elements. Specifically, the operating device 26 is used by the operator to operate the hydraulic actuators HA that drive the respective driven elements, and as a result, the operator can operate the driven elements that are the targets of the drive of the hydraulic actuators HA. The operating device 26 includes pedal devices and lever devices for operating the respective driven elements (hydraulic actuators HA).

For example, as shown in FIG. 4, the operating device 26 is of a hydraulic pilot type. Specifically, the operating device 26 uses hydraulic oil supplied from the pilot pump 15 through the pilot line 25 and the pilot line 25A branching therefrom, and outputs pilot pressure corresponding to the operation content to the secondary pilot line 27A. The pilot line 27A is connected to one inlet port of the shuttle valve 32, and is connected to the control valve 17 via the pilot line 27 connected to the outlet port of the shuttle valve 32. As a result, pilot pressure corresponding to the operation content related to various driven elements (hydraulic actuators HA) in the operating device 26 can be input to the control valve 17 via the shuttle valve 32. Therefore, the control valve 17 can drive each hydraulic actuator HA according to the operation content of the operating device 26 by the operator, etc.

The operating device 26 may also be electric. In this case, the pilot line 27A, the shuttle valve 32, and the hydraulic control valve 33 are omitted. Specifically, the operating device 26 outputs an electric signal (hereinafter, "operation signal") according to the operation content, and the operation signal is input to the controller 30. The controller 30 then outputs a control command according to the operation signal, that is, a control signal according to the operation content for the operating device 26, to the hydraulic control valve 31. As a result, a pilot pressure according to the operation content of the operating device 26 is input from the hydraulic control valve 31 to the control valve 17, and the control valve 17 can drive each hydraulic actuator HA according to the operation content of the operating device 26.

The control valves (directional control valves) built into the control valve 17 that drive the hydraulic actuators HA may be of the electromagnetic solenoid type. In this case, the operation signal output from the operating device 26 may be directly input to the control valve 17 (i.e., to the electromagnetic solenoid type control valve).

Also, as described above, part or all of the hydraulic actuator HA may be replaced with an electric actuator. In this case, the controller 30 may output a control command to the electric actuator or a driver that drives the electric actuator according to the operation content of the operating device 26 or the remote operation content specified by the remote operation signal. Also, when the excavator 100 is remotely operated, the operating device 26 may be omitted.

The hydraulic control valve 31 is provided for each driven element (hydraulic actuator HA) to be operated by the operating device 26 and for each driving direction of the driven element (hydraulic actuator HA) (for example, the lifting direction and the lowering direction of the boom 4). For example, two hydraulic control valves 31 are provided for each double-acting hydraulic actuator HA for driving the lower traveling body 1, the upper rotating body 3, the boom 4, the arm 5, the bucket 6, etc. The hydraulic control valve 31 may be provided, for example, in the pilot line 25B between the pilot pump 15 and the control valve 17, and may be configured to change its flow area (i.e., the cross-sectional area through which the hydraulic oil can flow). As a result, the hydraulic control valve 31 can output a predetermined pilot pressure to the secondary pilot line 27B using the hydraulic oil of the pilot pump 15 supplied through the pilot line 25B. Therefore, the hydraulic control valve 31 can indirectly apply a predetermined pilot pressure corresponding to a control signal from the controller 30 to the control valve 17 through the shuttle valve 32 between the pilot line 27B and the pilot line 27. Therefore, for example, the controller 30 can supply pilot pressure from the hydraulic control valve 31 to the control valve 17 in response to an operation command corresponding to the automatic driving function, thereby realizing the operation of the excavator 100 using the automatic driving function.

The controller 30 may also control the hydraulic control valve 31 to realize remote operation of the excavator 100. Specifically, the controller 30 outputs a control signal corresponding to the content of the remote operation specified by the remote operation signal received from the remote operation support device 400 to the hydraulic control valve 31 via the communication device 60. As a result, the controller 30 can supply pilot pressure corresponding to the content of the remote operation from the hydraulic control valve 31 to the control valve 17, thereby realizing the operation of the excavator 100 based on the remote operation of the operator.

In addition, when the operating device 26 is electric, the controller 30 can supply pilot pressure corresponding to the operation content (operation signal) of the operating device 26 directly to the control valve 17 from the hydraulic control valve 31, thereby realizing the operation of the excavator 100 based on the operation of the operator.

The shuttle valve 32 has two inlet ports and one outlet port, and outputs hydraulic oil having the higher pilot pressure of the two pilot pressures input to the inlet ports to the outlet port. The shuttle valve 32 is provided for each driven element (hydraulic actuator HA) to be operated by the operating device 26 and for each driving direction of the driven element (hydraulic actuator HA) in the same manner as the hydraulic control valve 31. For example, two shuttle valves 32 are provided for each double-acting hydraulic actuator HA for driving the lower traveling body 1, the upper rotating body 3, the boom 4, the arm 5, the bucket 6, etc. One of the two inlet ports of the shuttle valve 32 is connected to the secondary pilot line 27A of the operating device 26 (specifically, the above-mentioned lever device and pedal device included in the operating device 26), and the other is connected to the secondary pilot line 27B of the hydraulic control valve 31. The outlet port of the shuttle valve 32 is connected to the pilot port of the corresponding control valve of the control valve 17 through the pilot line 27. The corresponding control valve is a control valve that drives the hydraulic actuator HA that is the operation target of the above-mentioned lever device or pedal device connected to one inlet port of the shuttle valve 32. Therefore, each of these shuttle valves 32 can apply the higher of the pilot pressure of the pilot line 27A on the secondary side of the operating device 26 and the pilot pressure of the pilot line 27B on the secondary side of the hydraulic control valve 31 to the pilot port of the corresponding control valve. In other words, the controller 30 can control the corresponding control valve regardless of the operator's operation of the operating device 26 by outputting a pilot pressure higher than the pilot pressure on the secondary side of the operating device 26 from the hydraulic control valve 31. Therefore, the controller 30 can control the operation of the driven elements (lower traveling body 1, upper rotating body 3, boom 4, arm 5, bucket 6) regardless of the operating state of the operating device 26 by the operator, thereby realizing an automatic driving function or a remote operation function.

The hydraulic control valve 33 is provided in the pilot line 27A connecting the operating device 26 and the shuttle valve 32. The hydraulic control valve 33 is configured to be able to change its flow area, for example. The hydraulic control valve 33 operates in response to a control signal input from the controller 30. As a result, the controller 30 can forcibly reduce the pilot pressure output from the operating device 26 when the operating device 26 is operated by the operator. Therefore, even when the operating device 26 is being operated, the controller 30 can forcibly suppress or stop the operation of the hydraulic actuator HA corresponding to the operation of the operating device 26. In addition, the controller 30 can reduce the pilot pressure output from the operating device 26 to be lower than the pilot pressure output from the hydraulic control valve 31, for example, even when the operating device 26 is being operated. Therefore, the controller 30 can reliably apply the desired pilot pressure to the pilot port of the control valve in the control valve 17, for example, regardless of the operation content of the operating device 26, by controlling the hydraulic control valve 31 and the hydraulic control valve 33. Therefore, for example, the controller 30 can more appropriately realize the automatic operation function and remote control function of the excavator 100 by controlling the hydraulic control valve 33 in addition to the hydraulic control valve 31.

<User Interface>
As shown in FIG. 4 , the user interface system of the shovel 100 includes an operation device 26 , an output device 50 , and an input device 52 .

The output device 50 outputs various information to a user of the excavator 100 (e.g., an operator of the cabin 10 or an external remote control operator) and people in the vicinity of the excavator 100 (e.g., a worker or a driver of a work vehicle).

For example, the output device 50 includes lighting equipment and a display device 50A (see FIG. 7) that output various information in a visual manner. The lighting equipment is, for example, a warning light (indicator lamp), etc. The display device 50A is, for example, a liquid crystal display or an organic EL (Electroluminescence) display, etc. For example, as shown in FIG. 2, the lighting equipment and the display device 50A may be provided inside the cabin 10 and output various information in a visual manner to an operator, etc. inside the cabin 10. The lighting equipment and the display device 50A may also be provided, for example, on the side of the upper rotating body 3 and output various information in a visual manner to workers, etc. around the excavator 100.

The output device 50 may also include a sound output device that outputs various information in an auditory manner. Sound output devices include, for example, a buzzer or a speaker. The sound output device may be provided, for example, at least one of the inside and outside of the cabin 10, and may output various information in an auditory manner to an operator inside the cabin 10 or to people (workers, etc.) around the excavator 100.

The output device 50 may also include a device that outputs various information in a tactile manner, such as by vibration of the cockpit.

The input device 52 accepts various inputs from the user of the excavator 100, and signals corresponding to the accepted inputs are taken into the controller 30. For example, as shown in FIG. 2, the input device 52 is provided inside the cabin 10 and accepts inputs from an operator or the like inside the cabin 10. The input device 52 may also be provided, for example, on the side of the upper rotating body 3 and accept inputs from workers or the like in the vicinity of the excavator 100.

For example, the input device 52 includes an operation input device that accepts input from a user through mechanical operation. The operation input device may include a touch panel mounted on the display device 50A, a touch pad installed around the display device 50A, a button switch, a lever, a toggle, a knob switch provided on the operation device 26 (lever device), etc.

The input device 52 may also include an audio input device that accepts audio input from the user. The audio input device may include, for example, a microphone.

The input device 52 may also include a gesture input device that accepts gesture input from the user. The gesture input device includes, for example, an imaging device that captures an image of a gesture made by the user.

The input device 52 may also include a biometric input device that accepts biometric input from the user. The biometric input includes, for example, input of biometric information such as the user's fingerprint or iris.

<Communications>
As shown in FIG. 4 , the communication system of the shovel 100 according to this embodiment includes a communication device 60 .

The communication device 60 connects to an external communication line NW and communicates with a device provided separately from the shovel 100. The device provided separately from the shovel 100 may include a device outside the shovel 100, as well as a portable terminal device (mobile terminal) brought into the cabin 10 by the user of the shovel 100. The communication device 60 may include, for example, a mobile communication module conforming to standards such as 4G ( ^4th Generation) and 5G ( ^5th Generation). The communication device 60 may also include, for example, a satellite communication module. The communication device 60 may also include, for example, a WiFi communication module or a Bluetooth (registered trademark) communication module. When there are multiple connectable communication lines NW, the communication device 60 may include multiple communication devices according to the types of the communication lines NW.

For example, the communication device 60 communicates with external devices such as the information processing device 200 and the remote operation support device 400 at the work site through a local communication line established at the work site. The local communication line is, for example, a local 5G (so-called local 5G) mobile communication line established at the work site or a local network using Wi-Fi 6.

The communication device 60 may also communicate with an information processing device 200 or a remote operation support device 400 outside the work site through a wide area communication line that includes the work site, i.e., a wide area network.

<Control System>
4, the control system of the shovel 100 includes a controller 30. The control system of the shovel 100 according to this embodiment also includes an operating pressure sensor 29, a sensor 40, and sensors S1 to S9.

The controller 30 performs various controls related to the excavator 100.

The functions of the controller 30 may be realized by any hardware or any combination of hardware and software. For example, as shown in FIG. 3, the controller 30 includes an auxiliary storage device 30A, a memory device 30B, a CPU (Central Processing Unit) 30C, and an interface device 30D, which are connected by a bus BS1.

The auxiliary storage device 30A is a non-volatile storage means that stores the programs to be installed as well as necessary files and data. The auxiliary storage device 30A is, for example, an EEPROM (Electrically Erasable Programmable Read-Only Memory) or a flash memory.

For example, when an instruction to start a program is received, the memory device 30B loads the program from the auxiliary storage device 30A so that the program can be read by the CPU 30C. The memory device 30B is, for example, a static random access memory (SRAM).

The CPU 30C executes, for example, a program loaded into the memory device 30B and performs various functions of the controller 30 according to the program's instructions.

The interface device 30D functions, for example, as a communication interface for connecting to a communication line inside the excavator 100. The interface device 30D may include multiple different types of communication interfaces according to the type of communication line to be connected.

The interface device 30D also functions as an external interface for reading data from a recording medium and writing data to the recording medium. The recording medium is, for example, a dedicated tool connected to a connector installed inside the cabin 10 via a detachable cable. The recording medium may also be a general-purpose recording medium such as an SD memory card or a USB (Universal Serial Bus) memory. As a result, a program that realizes various functions of the controller 30 can be provided, for example, by a portable recording medium and installed in the auxiliary storage device 30A of the controller 30. The program may also be downloaded from another computer (for example, the information processing device 200) outside the excavator 100 through the communication device 60 and installed in the auxiliary storage device 30A.

Note that some of the functions of the controller 30 may be realized by another controller (control device). In other words, the functions of the controller 30 may be realized in a distributed manner by multiple controllers mounted on the excavator 100.

The operating pressure sensor 29 detects the pilot pressure on the secondary side (pilot line 27A) of the hydraulic pilot type operating device 26, i.e., the pilot pressure corresponding to the operating state of each driven element (hydraulic actuator) in the operating device 26. The detection signal of the pilot pressure by the operating pressure sensor 29 corresponding to the operating state of each driven element (hydraulic actuator HA) in the operating device 26 is input to the controller 30.

If the operating device 26 is an electrical type, the operating pressure sensor 29 is omitted. This is because the controller 30 can grasp the operating state of each driven element through the operating device 26 based on the operating signal received from the operating device 26.

The sensor 40 acquires measurement data, for example, regarding the shape of objects around the shovel 100.

For example, the sensor 40 is a shape sensor, such as a distance sensor or a 3D camera, capable of acquiring measurement data representing the shape of objects around the shovel 100. The sensor 40 may also be an integrated sensor that has the function of a characteristic sensor, such as a multi-wavelength spectroscopic camera, capable of acquiring measurement data representing the characteristics of objects around the shovel 100, in addition to the function of a shape sensor.

2, the sensor 40 includes sensors 40F, 40B, 40L, and 40R. Sensor 40F measures the state (shape and characteristics) of an object in front of the upper rotating body 3. Sensor 40B measures the state of an object on the upper rotating body 3. Sensor 40L measures the state of an object to the left of the upper rotating body 3. Sensor 40R measures the state of an object to the right of the upper rotating body 3. In this way, the sensor 40 can measure the state of objects in a range around the shovel 100, that is, in an angular direction of 360 degrees, when viewed from above the shovel 100. Hereinafter, the sensors 40F, 40B, 40L, and 40R may be collectively or individually referred to as "sensor 40X."

The output data of the sensor 40 (sensor 40X) (i.e., measurement data relating to the state of objects around the shovel 100) is input to the controller 30 via a one-to-one communication line or an on-board network. This allows the controller 30 to grasp, for example, the shape, characteristics, and other state of objects around the shovel 100 based on the output data of the sensor 40X.

In addition, some or all of the sensors 40B, 40L, and 40R may be omitted.

The sensor S1 is attached to the boom 4 and measures the attitude of the boom 4. The sensor S1 outputs measurement data representing the attitude of the boom 4. The attitude of the boom 4 is, for example, the attitude angle around the rotation axis of the base end corresponding to the connection part of the boom 4 with the upper rotating body 3 (hereinafter, "boom angle"). The sensor S1 includes, for example, a rotary potentiometer, a rotary encoder, an acceleration sensor, an angular acceleration sensor, a 6-axis sensor, an IMU (Inertial Measurement Unit), etc. The same may be true for the sensors S2 to S4 below. The sensor S1 may also include a cylinder sensor that detects the extension/retraction position of the boom cylinder 7. The same may be true for the sensors S2 and S3 below. The output of the sensor S1 (measurement data representing the attitude of the boom 4) is taken into the controller 30. This allows the controller 30 to grasp the attitude of the boom 4.

Sensor S2 is attached to arm 5 and measures the posture of arm 5. Sensor S2 outputs measurement data representing the posture of arm 5. The posture of arm 5 is, for example, the posture angle around the rotation axis of the base end corresponding to the connection part of arm 5 with boom 4 (hereinafter referred to as "arm angle"). The output of sensor S2 (measurement data representing the posture of arm 5) is input to controller 30. This allows controller 30 to grasp the posture of arm 5.

Sensor S3 is attached to bucket 6 and measures the attitude of bucket 6. Sensor S3 outputs measurement data that indicates the attitude of bucket 6. The attitude of bucket 6 is, for example, the attitude angle (hereinafter, "arm angle") around the rotation axis of the base end that corresponds to the connection part of bucket 6 with arm 5. The output of sensor S3 (measurement data that indicates the attitude of bucket 6) is input to controller 30. This allows controller 30 to grasp the attitude of bucket 6.

The sensor S4 measures the attitude of the shovel 100's body (e.g., the upper rotating body 3). The sensor S4 outputs measurement data representing the attitude of the shovel 100's body. The attitude of the shovel 100's body is, for example, the inclination of the body relative to a predetermined reference plane (e.g., a horizontal plane). For example, the sensor S4 is attached to the upper rotating body 3 and measures the inclination angles of the shovel 100 around two axes in the front-rear and left-right directions (hereinafter, "front-rear inclination angle" and "left-right inclination angle"). The output of the sensor S4 (measurement data representing the attitude of the shovel 100's body) is input to the controller 30. This allows the controller 30 to grasp the attitude (inclination) of the body (upper rotating body 3).

The sensor S5 is attached to the upper rotating body 3 and measures the rotation state of the upper rotating body 3. The sensor S5 outputs measurement data representing the rotation state of the upper rotating body 3. The sensor S5 measures, for example, the rotation angular velocity and rotation angle of the upper rotating body 3. The sensor S5 includes, for example, a gyro sensor, a resolver, a rotary encoder, etc. The output of the sensor S5 (measurement data representing the rotation state of the upper rotating body 3) is input to the controller 30. This allows the controller 30 to grasp the rotation state of the upper rotating body 3, such as the rotation angle.

The controller 30 can grasp (estimate) the position of the tip of the attachment AT (bucket 6) based on the output of sensors S1 to S5.

If sensor S4 includes a gyro sensor, a six-axis sensor, an IMU, or the like capable of detecting angular velocity around three axes, the rotation state (e.g., rotation angular velocity) of the upper rotating body 3 may be detected based on the detection signal of sensor S4. In this case, sensor S5 may be omitted.

The sensor S6 measures the position of the shovel 100. The sensor S6 may measure the position in world (global) coordinates, or may measure the position in local coordinates at the work site. In the former case, the sensor S6 is, for example, a Global Navigation Satellite System (GNSS) sensor. In the latter case, the sensor S6 is a transceiver that communicates with a device that serves as a reference for the position at the work site and can output a signal corresponding to the position relative to the reference. The output of the sensor S6 is taken into the controller 30.

Sensor S7 measures the pressure (cylinder pressure) in the oil chamber of boom cylinder 7. Sensor S7 includes, for example, a sensor that measures the cylinder pressure (rod pressure) in the oil chamber on the rod side of boom cylinder 7, and a sensor that measures the cylinder pressure (bottom pressure) in the oil chamber on the bottom side. The output of sensor S7 (measurement data of the cylinder pressure of boom cylinder 7) is input to controller 30.

Sensor S8 measures the pressure (cylinder pressure) in the oil chamber of arm cylinder 8. Sensor S8 includes, for example, a sensor that measures the cylinder pressure (rod pressure) in the oil chamber on the rod side of arm cylinder 8, and a sensor that measures the cylinder pressure (bottom pressure) in the oil chamber on the bottom side of arm cylinder 8. The output of sensor S8 (measurement data for the cylinder pressure of arm cylinder 8) is taken into controller 30.

Sensor S9 measures the pressure (cylinder pressure) in the oil chamber of bucket cylinder 9. Sensor S9 includes, for example, a sensor that measures the cylinder pressure (rod pressure) in the oil chamber on the rod side of bucket cylinder 9, and a sensor that measures the cylinder pressure (bottom pressure) in the oil chamber on the bottom side of bucket cylinder 9. The output of sensor S9 (measurement data of the cylinder pressure of bucket cylinder 9) is input to controller 30.

The controller 30 can grasp the load state acting on the attachment AT based on the output of the sensors S7 to S9. The load acting on the attachment AT includes, for example, the reaction force acting on the bucket 6 from the work target (soil on the ground) and the weight of the soil contained in the bucket 6.

<Hardware configuration of information processing device>
FIG. 5 is a block diagram showing an example of a hardware configuration of the information processing device 200. As shown in FIG.

The functions of the information processing device 200 are realized by any hardware or any combination of hardware and software. For example, as shown in FIG. 5, the information processing device 200 includes an external interface 201, an auxiliary storage device 202, a memory device 203, a CPU 204, a high-speed calculation device 205, a communication interface 206, an input device 207, a display device 208, and a sound output device 209. These are connected by a bus BS2.

The external interface 201 functions as an interface for reading data from the recording medium 201A and writing data to the recording medium 201A. Examples of the recording medium 201A include flexible disks, CDs (Compact Discs), DVDs (Digital Versatile Discs), BDs (Blu-ray (registered trademark) Discs), SD memory cards, USB memories, and the like. This allows the information processing device 200 to read various data used in processing through the recording medium 201A, store the data in the auxiliary storage device 202, and install programs that realize various functions.

In addition, the information processing device 200 may obtain various data and programs used in processing from an external device via the communication interface 206.

The auxiliary storage device 202 stores various installed programs as well as files and data necessary for various processes. The auxiliary storage device 202 includes, for example, a hard disk drive (HDD), a solid state disk (SSD), flash memory, etc.

When an instruction to start a program is received, the memory device 203 reads the program from the auxiliary storage device 202 and stores it. The memory device 203 includes, for example, a dynamic random access memory (DRAM) or an SRAM.

The CPU 204 executes various programs loaded from the auxiliary storage device 202 to the memory device 203, and realizes various functions related to the information processing device 200 in accordance with the programs.

The high-speed calculation device 205 works in conjunction with the CPU 204 to perform calculation processing at a relatively high speed. The high-speed calculation device 205 includes, for example, a GPU (Graphics Processing Unit), an ASIC (Application Specific Integrated Circuit), an FPGA (Field-Programmable Gate Array), etc.

The high-speed calculation device 205 may be omitted depending on the required calculation processing speed.

The communication interface 206 is used as an interface for connecting to an external device so as to be able to communicate with the device. This allows the information processing device 200 to communicate with an external device, such as the shovel 100, through the communication interface 206. The communication interface 206 may also have multiple types of communication interfaces depending on the communication method between the connected device, etc.

The input device 207 accepts various inputs from the user. The input device 207 includes a remote control operation device for remotely operating the excavator 100.

The input device 207 includes, for example, an input device that accepts mechanical operation input from a user (hereinafter, "operation input device"). The operation device for remote operation may be an operation input device. The operation input device includes, for example, a button, a toggle, a lever, a keyboard, a mouse, a touch panel implemented in the display device 208, a touch pad provided separately from the display device 208, etc.

The input device 207 may also include a voice input device capable of receiving voice input from a user. The voice input device may include, for example, a microphone capable of collecting the user's voice.

The input device 207 may also include a gesture input device capable of accepting gesture input from a user. The gesture input device includes, for example, a camera capable of capturing an image of the user's gesture.

The input device 207 may also include a biometric input device capable of accepting biometric input from a user. The biometric input device includes, for example, a camera capable of acquiring image data containing information about the user's fingerprint or iris.

The display device 208 displays an information screen and an operation screen for a user of the information processing device 200. The display device 208 is, for example, a liquid crystal display or an organic EL (Electroluminescence) display.

The sound output device 209 conveys various information to the user of the information processing device 200 by sound. The sound output device 209 is, for example, a buzzer, an alarm, a speaker, etc.

[Functional configuration of the operation support system]
Next, the functional configuration of the operation support system SYS will be described with reference to Fig. 6 and Fig. 7 in addition to Fig. 1 to Fig. 5. Specifically, the functional configuration related to generation of a trajectory of a working part of the excavator 100 in the operation support system SYS will be described.

<First Example>
FIG. 6 is a functional block diagram showing a first example of the functional configuration of the operation support system SYS.

Hereinafter, the term "the trajectory of the working part of the shovel 100" is used to include both the path (i.e., the track) that the working part of the shovel 100 has already traveled, and the path that it may travel in the future. The working part corresponds to the tip of the AT attachment that is used to make changes to the work target. Specifically, the working part is the bucket 6.

The shovel 100 includes an assistance device 150. In this example, the assistance device 150 provides assistance to the shovel 100 operating using an autonomous driving function in carrying out tasks.

As shown in FIG. 6, the support device 150 includes a controller 30, a hydraulic control valve 31, a sensor 40, and sensors S1 to S9.

The controller 30 includes, as functional units, an operation log providing unit 301 and a work support unit 302.

When the operation support system SYS includes a plurality of shovels 100, there may be shovels 100 in which the controller 30 includes only the operation log providing unit 301 and the work support unit 302, and shovels 100 in which the controller 30 includes only the latter. In this case, the former shovel 100 only has the function of acquiring the operation log of the shovel 100 and providing it to the information processing device 200, which is used for the work support function of the latter shovel 100. The same may be true for the second example described below.

The information processing device 200 includes, as functional units, a log acquisition unit 2001, a simulator unit 2002, a log storage unit 2003, a teacher data generation unit 2004, a machine learning unit 2005, a trained model storage unit 2006, and a distribution unit 2007.

The operation log providing unit 301 is a functional unit for acquiring operation logs during specific operations of the excavator 100 and providing them to the information processing device 200.

The predetermined operation includes, for example, an excavation operation, a boom-raising and rotating operation, a boom-lowering and rotating operation, a soil dumping operation, a broom operation, etc., which are used during excavation work. The predetermined operation may also include an excavation operation, a soil dumping operation, a sweeping operation, a horizontal pulling operation, a rolling operation, a broom operation, etc., which are used during ground leveling work. The predetermined operation may also include a cutting operation, a rolling operation, etc., which are used during slope work. The sweeping operation is, for example, an operation in which the attachment AT is operated and the bucket 6 is pushed forward along the ground, thereby sweeping soil and sand forward with the back of the bucket 6. In the sweeping operation, for example, the attachment AT performs a lowering operation of the boom 4 and an opening operation of the arm 5. The horizontal pulling operation is, for example, an operation in which the attachment AT is operated and the tip of the bucket 6 is moved so as to be pulled toward the front substantially horizontally along the ground, thereby leveling out the unevenness of the ground (surface of the terrain). In the horizontal pulling operation, for example, the attachment AT performs a raising operation of the boom 4 and a closing operation of the arm 5. The rolling operation is, for example, an operation of operating the attachment AT and pressing the ground with the back surface of the bucket 6. The rolling operation may also be an operation of pressing the ground by striking the back surface of the bucket 6 against the ground while moving the bucket 6 up and down. The rolling operation may also be an operation of pushing the bucket 6 forward along the ground, sweeping the soil and sand to a predetermined position forward with the back surface of the bucket 6, and then pressing the ground at the predetermined position with the back surface of the bucket 6. In the rolling operation, for example, the attachment AT performs a lowering operation of the boom 4 when pressing the ground. The broom operation is, for example, an operation of operating the upper rotating body 3 and rotating the bucket 6 left and right while it is aligned with the ground. The broom operation may also be an operation of operating the attachment AT and the upper rotating body 3 and pushing the bucket 6 forward while rotating the bucket 6 alternately left and right while it is aligned with the ground. In the broom operation, for example, the upper rotating body 3 alternately repeats left and right rotating operations. In addition, in the broom operation, for example, in addition to the alternating left and right rotation of the upper rotating body 3, the attachment AT may lower the boom 4 and open the arm 5, as in the sweeping operation.

The operation log of the shovel 100 is time-series data representing the operating state of the shovel 100. For example, the operation log of the shovel 100 includes time-series data representing the operation contents of the operator. The time-series data representing the operation contents of the operator is, for example, time-series output data of the operating pressure sensor 29 corresponding to the hydraulic pilot type operating device 26 or time-series output data (operation signal data) of the operating device 26 corresponding to the electric type operating device 26. The operation log of the shovel 100 may also be time-series output data of the sensors S1 to S5 or time-series data representing the posture state of the shovel 100 acquired from the output data of the sensors S1 to S5.

For example, the operation log providing unit 301 acquires an operation log when an operator who has a long history of operating the shovel 100 and is relatively experienced (hereinafter, for convenience, referred to as an "expert") operates the shovel 100, and provides the operation log to the information processing device 200. As a result, as described below, a learned model LM2 capable of reproducing the operation of the shovel 100 operated by an expert can be generated by machine learning based on the operation log of the shovel 100.

Also, as described below, the learned model LM2 may be omitted and only the learned model LM1 may be generated. In this case, the operation log of the shovel 100 provided to the information processing device 200 may include an operation log when an operator other than an expert operates the shovel 100, or may include an operation log corresponding to the operation of the shovel 100 by the automatic driving function. Also, the operation log of the shovel 100 for the learned model LM1 and the operation log of the shovel 100 for the learned model LM2 may be acquired separately.

The operation log providing unit 301 includes an operation log recording unit 301A, an operation log storage unit 301B, and an operation log transmission unit 301C.

The operation log recording unit 301A acquires an operation log during a specific operation of the shovel 100 and records it in the operation log storage unit 301B. For example, each time a specific operation of the shovel 100 is performed, the operation log recording unit 301A records the operation log during that operation in the operation log storage unit 301B.

The operation log storage unit 301B stores the operation log of the shovel 100. For example, the operation log storage unit 301B stores the operation log and the data of the time (date and time) when the predetermined operation was performed for each predetermined operation performed by the shovel 100, linked to each other. The data of the time when the predetermined operation was performed includes data of both the start and end times of the predetermined operation of the shovel 100. Furthermore, when multiple predetermined operations are specified, the operation log storage unit 301B stores the operation log, the data of the time when the predetermined operation was performed, and the data of the identification information of the performed predetermined operation, linked to each other, for each predetermined operation performed by the shovel 100. Hereinafter, the data linked to the operation log of the shovel 100 may be referred to as "associated data" for convenience. For example, the operation log storage unit 301B stores record data representing the correspondence between the operation log and the associated data for each predetermined operation performed by the shovel 100, thereby constructing a database of the operation log when the predetermined operation of the shovel 100 is performed.

In addition, the operation log of the operation log storage unit 301B that has already been transmitted to the information processing device 200 by the operation log transmission unit 301C described below may be erased later.

The operation log transmission unit 301C transmits the operation log stored in the operation log storage unit 301B when the shovel 100 performs a predetermined operation and the associated data linked to the operation log to the information processing device 200 via the communication device 60. The operation log transmission unit 301C may also transmit record data indicating the correspondence between the operation log of the shovel 100 and the associated data for each predetermined operation performed by the shovel 100 to the information processing device 200.

For example, the operation log transmission unit 301C transmits the untransmitted operation log and associated data of the shovel 100 stored in the operation log storage unit 301B to the information processing device 200 in response to a request to transmit the operation log of the shovel 100 received from the information processing device 200. The operation log transmission unit 301C may also automatically transmit the untransmitted operation log and associated data of the shovel 100 stored in the operation log storage unit 301B to the information processing device 200 at a predetermined timing. The predetermined timing is, for example, when the shovel 100 stops operating (key switch off) or starts operating (key switch on), etc.

The log acquisition unit 2001 acquires logs when the excavator 100 performs a specified operation.

The log when the shovel 100 performs a predetermined operation includes an operation log when the shovel 100 performs the predetermined operation and a status log of the work object. The status log of the work object includes data representing the status of the work object before and after the shovel 100 performs the predetermined operation. The status of the work object includes the shape of the soil (topography) of the work object and the properties of the soil. The operation log when the shovel 100 performs a predetermined operation is uploaded from the shovel 100. The status log of the work object when the shovel 100 performs a predetermined operation is obtained based on the measurement data uploaded from the sensor group 300 and the associated data uploaded from the shovel 100 (data of the time when the predetermined operation was performed).

The simulator unit 2002 performs a computer simulation of a specific operation of the shovel 100 using a virtual model of the shovel 100 and the work object (soil and sand).

For example, the distinct element method (DEM) is used to model the soil on the ground as a collection of minute particles. This allows the simulator unit 2002 to virtually reproduce the overall behavior of the soil as a collection and the reaction force from the soil by having the virtual model of the shovel 100 perform a specified operation such as an excavation operation and analyzing the individual movements of the minute particles.

The simulator unit 2002 acquires data on the trajectory of the working part of the shovel 100 and data on the state of the work object (soil and sand) before and after the execution of the specified operation as a log when the shovel 100 executes a specified operation through computer simulation. The former data corresponds to an operation log when the shovel 100 executes a specified operation through computer simulation, and the latter data corresponds to a state log of the work object when the shovel 100 executes a specified operation through computer simulation.

The simulator unit 2002 performs computer simulations of numerous patterns of a predetermined operation of the shovel 100 using various conditions of the work object (soil and sand) and various trajectories of the working parts of the shovel 100. This allows the simulator unit 2002 to accumulate in the log storage unit 2003 logs of when the shovel 100 performs a predetermined operation through computer simulation under mutually different conditions.

The log storage unit 2003 stores logs acquired by the log acquisition unit 2001 and the simulator unit 2002 when the shovel 100 performs a predetermined operation in an accumulated form. For example, the log storage unit 2003 stores an operation log for each predetermined operation actually performed by the shovel 100 or performed by computer simulation, a status log of the work target, and associated data in a linked form. In the log storage unit 2003, the logs acquired by the log acquisition unit 2001 and the logs acquired by the simulator unit 2002 may be stored in an identifiable manner, or may be stored mixed together in an indistinguishable manner.

The teacher data generation unit 2004 generates teacher data for machine learning based on the log of when the excavator 100 performs a predetermined operation stored in the log storage unit 2003, and outputs a teacher data set that is a collection of a large number of teacher data. The teacher data generation unit 2004 may automatically generate teacher data by batch processing, or may generate teacher data in response to input from a user of the information processing device 200. The teacher data generation unit 2004 includes teacher data generation units 2004A and 2004B.

The teacher data generation unit 2004A generates a teacher data set for generating the trained model LM1. The trained model LM1 infers the shape of the work object after the shovel 100 performs the specified operation, using as input data data on the shape of the work object before the shovel 100 performs the specified operation and data on the trajectory (track) of the work part when the shovel 100 performs the specified operation. The teacher data is a combination of the state of the work object before the shovel 100 performs the specified operation and the trajectory of the work part when the shovel 100 performs the specified operation as input data, and the state of the work object after the specified operation as correct answer data.

The input data of the trained model LM1 may also include data representing the characteristics of the soil that is the object of work by the shovel 100. For example, the data representing the characteristics of the soil includes data on the angle of repose of the soil. This allows the trained model LM1 to infer a more appropriate soil shape by taking into account the angle of repose of the soil. In this case, the input data in the training data includes data representing the characteristics of the soil (data on the angle of repose).

The input data of the trained model LM1 may also include data representing the excavation reaction force when the shovel 100 performs a specified operation. This allows the trained model LM1 to estimate an appropriate soil shape by taking the excavation reaction force into account, for example, in a case where the bucket 6 hits a rock or the like underground and as a result the soil cannot be excavated.

The teacher data set for generating the trained model LM1 may be generated from only the log acquired by the log acquisition unit 2001 and the log output from the simulator unit 2002. In this case, the simulator unit 2002 may be omitted. Similarly, the teacher data set for generating the trained model LM1 may be generated from only the log acquired by the log acquisition unit 2001 and the log output from the simulator unit 2002. In this case, the operation log providing unit 301 of the sensor group 300 and the shovel 100 may be omitted. In addition, the teacher data set for generating the trained model LM1 may include a base teacher data set and a teacher data set for final adjustment (fine tuning). In this case, since a large amount of data is required, the base teacher data set may be generated based on the log output from the simulator unit 2002, and the teacher data set for final adjustment may be generated based on the log acquired by the log acquisition unit 2001. The same may be true for the trained model LM2.

The teacher data generating unit 2004B generates teacher data for generating the trained model LM2. The trained model LM2 uses data on the state of the work object around the shovel 100 as input and infers the target trajectory of the working part in a predetermined operation of the shovel 100. The teacher data is a combination of the state of the work object before the execution of the predetermined operation of the shovel 100 as input data and the trajectory of the working part when the shovel 100 executes the predetermined operation by the operation of the expert as correct answer data. In other words, the teacher data generating unit 2004 generates a teacher data set based on the log acquired by the log acquiring unit 2001 when the shovel 100 performs the predetermined operation by the operation of the expert. In addition, when multiple types of predetermined operations are specified, the trained model LM2 may be generated for each type of predetermined operation. In this case, the teacher data generating unit 2004B generates a teacher data set for each type of predetermined operation.

The machine learning unit 2005 performs machine learning on the base learning model based on the teacher data set generated by the teacher data generation unit 2004, and generates trained models LM1 and LM2. The trained model (base learning model) includes, for example, a neural network such as a deep neural network (DNN).

The machine learning unit 2005 includes machine learning units 2005A and 2005B.

The machine learning unit 2005A performs machine learning on the base learning model M1 based on the teacher data set output from the teacher data generation unit 2004A. As a result, the machine learning unit 2005A can generate a learned model LM1 that can output (infer) the state of the work object after the execution of the specified operation of the shovel 100, using as input data on the state of the work object before the execution of the specified operation of the shovel 100 and data on the trajectory of the work part when the specified operation of the shovel 100 is executed. In addition, the machine learning unit 2005A may correct (additionally learn) the learned model LM1 so that the error between the inference result by the learned model LM1 and the actual measurement result of the sensor 40 is reduced. In this case, the inference result by the learned model LM1 and the data of the actual measurement result of the sensor 40 are uploaded from the shovel 100 to the information processing device 200.

The machine learning unit 2005B performs machine learning on the base learning model M2 based on the teacher data set output from the teacher data generation unit 2004B. This allows the machine learning unit 2005B to generate a learned model LM2 that is capable of outputting (inferring) a target trajectory of a working part in a specified operation of the shovel 100, using data on the state of the work object around the shovel 100 as input.

The trained model storage unit 2006 stores trained models LM1 and LM2 output by the machine learning unit 2005. Furthermore, when the trained model LM1 is re-trained or additionally trained by the machine learning unit 2005A, the trained model LM1 in the trained model storage unit 2006 is updated. The same applies when the trained model LM2 is re-trained or additionally trained by the machine learning unit 2005B.

The distribution unit 2007 distributes data of the trained models LM1 and LM2 to the excavator 100.

For example, when the machine learning unit 2005A generates or updates the trained model LM1, the distribution unit 2007 distributes the most recently generated or updated trained model LM1 to the shovel 100. In addition, the distribution unit 2007 may distribute the latest trained model LM1 in the trained model memory unit 2006 to the shovel 100 in response to a signal received from the shovel 100 requesting distribution of the trained model LM1. The same may be true for the trained model LM2.

The work support unit 302 is a functional unit for providing work support to the excavator 100 operating using an autonomous driving function.

The work support unit 302 includes a learned model storage unit 302A, a work object shape acquisition unit 302B, a target trajectory generation unit 302C, and a motion control unit 302D.

The trained model storage unit 302A stores trained models LM1 and LM2 that are distributed from the information processing device 200 and received via the communication device 60.

The work object shape acquisition unit 302B acquires data representing the shape of the soil being the work object of the shovel 100 based on the trajectory (track) of the working part when the shovel 100 performs a predetermined operation. Specifically, the work object shape acquisition unit 302B may acquire data representing the shape of the soil being the work object of the shovel 100 by estimating a change in the shape of the soil from before the execution of the predetermined operation based on the trajectory of the working part when the shovel 100 performs a predetermined operation. The work object shape acquisition unit 302B may also acquire data representing the shape of the soil being the work object of the shovel 100 by taking into account measurement data of the properties of the soil being the work object obtained by the sensor 40 (property sensor) and measurement data from the sensors S7 to S9 (reaction force from the soil being the work object to the work part).

At this time, the work object shape acquisition unit 302B may interpolate the shape of the soil at a location that cannot be measured by the sensor 40 based on the trajectory of the working part when the shovel 100 performs a predetermined operation, based on the measurement data of the shape of the soil of the work object by the sensor 40. Also, the work object shape acquisition unit 302B may acquire data representing the soil shape while estimating the change in the shape of the soil based on the trajectory of the working part for each execution of the predetermined operation of the shovel 100, based on the initial state of the shape of the soil of the work object of the shovel 100, without using the sensor 40. In this case, the sensor 40 may be omitted. The initial state of the shape of the soil of the work object of the shovel 100 is acquired, for example, by being distributed from outside the shovel 100 through the communication device 60, or by being input by the user through the input device 52. Also, the initial state of the shape of the soil of the work object of the shovel 100 may be fixed, for example, as a flat surface at the same height as the ground on which the crawler of the shovel 100 is installed.

For example, the work object shape acquisition unit 302B estimates the shape of the soil after the shovel 100 performs the specified operation using the learned model LM1 based on the shape of the soil before the shovel 100 performs the specified operation and the trajectory of the working part when the shovel 100 performs the specified operation. The work object shape acquisition unit 302B may then acquire data representing the current state of the work object by integrating the above estimation result with the measurement data of the soil shape after the shovel 100 performs the specified operation by the sensor 40. Specifically, the work object shape acquisition unit 302B performs data integration by interpolating the data of the above estimation result for points in the observation target area around the shovel 100 where the sensor 40 was unable to measure the soil shape. As a result, even if the sensor 40 is unable to acquire measurement data of the work object at a part of the observation target area due to occlusion or the like, the controller 30 can acquire data representing the shape of the soil of the work object in the observation target area, including the shape of the work object at that point.

The shape of the work object before the execution of a predetermined operation of the shovel 100 corresponds to, for example, the previous output by the work object shape acquisition unit 302B. The trajectory of the work part during the predetermined operation of the shovel 100 is acquired, for example, based on the output of the sensors S1 to S6.

In addition, when an obstacle is present in the observation target area around the shovel 100 based on the output of the sensor 40, the work object shape acquisition unit 302B may exclude the area where the obstacle exists from the estimation target of the shape of the soil to be worked on. The obstacle includes, for example, a moving body such as a work machine or a work vehicle, and a feature such as a utility pole or a fence. In addition, when there are multiple shovels 100 operating at the same work site, the multiple shovels 100 may share data representing the trajectory (track) of the working part when performing a predetermined operation. This allows the work object shape acquisition unit 302B (trained model LM1) to take into account changes in the shape of the soil to be worked on due to the predetermined operation of the other shovels 100. Therefore, the work object shape acquisition unit 302B (trained model LM1) can more appropriately estimate the shape of the soil to be worked on around the shovel 100. Part or all of the functions of the work object shape acquisition unit 302B may be transferred to an external device (e.g., the information processing device 200) with a relatively high processing capacity. As a result, even if the controller 30's own processing power is insufficient, it can obtain data representing the shape of the soil and sand to be worked on after the shovel 100 has performed the specified operation, taking into account the trajectory of the working part when the shovel 100 is performing the specified operation.

The target trajectory generating unit 302C generates a target trajectory for a specified operation of the shovel 100 based on the estimation result of the work object shape acquiring unit 302B (the state of the work object after the shovel 100 performs a specified operation).

For example, the target trajectory generation unit 302C uses the learned model LM2 to generate a target trajectory for the work part in a specified operation of the shovel 100 based on the shape of the soil to be worked on acquired by the work object shape acquisition unit 302B.

The target trajectory generating unit 302C may generate a target trajectory of the working part of the shovel 100 according to the state (prediction result) of the work target around the shovel 100 by applying any known method instead of the learned model LM2. In this case, the teacher data generating unit 2004C and the machine learning unit 2005B may be omitted. For example, the target trajectory generating unit 302C may generate data of the target trajectory of the working part of the shovel 100 by MPC (Model Predictive Control) based on the shape of the soil of the work target acquired by the work target shape acquiring unit 302B. The target trajectory generating unit 302C may generate data of the target trajectory of the working part of the shovel 100 by optimizing a predetermined reference trajectory of the working part of the shovel 100 based on the shape of the soil of the work target acquired by the work target shape acquiring unit 302B.

The operation control unit 302D causes the shovel 100 to perform a predetermined operation so that a predetermined part of the shovel 100 moves along the target trajectory generated by the target trajectory generating unit 302C. Specifically, the operation control unit 302D controls the hydraulic control valve 31 while grasping the position of the working part from the outputs of the sensors S1 to S5, etc., to cause the shovel 100 to perform a predetermined operation so that the working part of the shovel 100 moves along the target trajectory. This allows the shovel 100 to autonomously proceed with work while executing a predetermined operation in accordance with the shape of the work target.

In this way, in this example, the controller 30 acquires data representing the shape of the soil on the work target (ground) of the shovel 100 in accordance with the predetermined operation of the shovel 100. Specifically, the controller 30 acquires data representing the shape of the soil on the work target (ground) of the shovel 100 based on the trajectory (track) of the work part when the shovel 100 performs the predetermined operation. As a result, even in a situation where the sensor 40 cannot measure the soil shape due to occlusion or the like, the controller 30 can interpolate the soil shape at that location, taking into account the change in the soil shape accompanying the movement of the work part of the shovel 100. In addition, even without using the sensor 40, the soil shape of the work target of the shovel 100 can be estimated based on the history of the change in the soil shape accompanying the movement of the work part of the shovel 100. Therefore, the controller 30 can more appropriately grasp the soil shape of the work target of the shovel 100 in the observation target area, and as a result, can more appropriately generate the target trajectory of the work part of the shovel 100. Therefore, the controller 30 can more appropriately perform autonomous operation of the excavator 100.

In addition, some or all of the functions of the work object shape acquisition unit 302B, the target trajectory generation unit 302C, and the operation control unit 302D may be transferred to the information processing device 200. This makes it possible to reduce the processing load on the shovel 100 for processing related to the generation of the target trajectory of the working part of the shovel 100 and processing related to the control of the operation of the shovel 100.

<Second Example>
FIG. 7 is a functional block diagram showing a second example of the functional configuration of the operation support system SYS.

In the following, the same reference numerals will be used for configurations that are the same as or correspond to those in the first example described above, and the explanation will focus on the differences from the first example described above.

The shovel 100 includes an assistance device 150, as in the first example described above. In this example, the assistance device 150 assists a user who operates the shovel 100 to perform work, or who monitors the work of the shovel 100.

As shown in FIG. 7, in this example, the support device 150 includes a controller 30, a sensor 40, a display device 50A, and sensors S1 to S9. In addition, when the shovel 100 is remotely operated, the support device 150 may include a communication device 60.

The controller 30 includes, as functional units, an operation log providing unit 301 and a work support unit 302, similar to the first example described above.

The operation log providing unit 301 includes an operation log recording unit 301A, an operation log storage unit 301B, and an operation log transmission unit 301C, similar to the first example described above.

The information processing device 200 includes, as functional units, a log acquisition unit 2001, a simulator unit 2002, a log storage unit 2003, a teacher data generation unit 2004, a machine learning unit 2005, a trained model storage unit 2006, and a distribution unit 2007, similar to the first example described above.

In this example, the information processing device 200 differs from the first example described above in that the teacher data generation unit 2004B, the machine learning unit 2005B, and the trained model LM2 are omitted.

The work support unit 302 is a functional unit for providing support to a user who operates the shovel 100 to perform work or monitors the work of the shovel 100.

The work support unit 302 includes a learned model storage unit 302A, a work object shape acquisition unit 302B, and a display processing unit 302E. In other words, the work support unit 302 differs from the first example described above in that the target trajectory generation unit 302C and the motion control unit 302D are omitted, and a display processing unit 302E is added.

The display processing unit 302E causes the display device 50A to display a screen related to work support for a user who operates the shovel 100 to perform work, or who monitors the work of the shovel 100. The display processing unit 302E may also transmit data corresponding to a similar screen to the remote operation support device 400 or the remote monitoring support device via the communication device 60, and cause the data to be displayed on the remote operation support device 400 or the remote monitoring support device.

For example, the display processing unit 302E displays an image representing the shape of the soil of the work target (ground) of the shovel 100 on the display device 50A based on the output of the work target shape acquisition unit 302B (data on the shape of the soil of the work target after the shovel 100 performs a predetermined operation). The display processing unit 302E may also transmit image data representing the shape of the soil of the work target of the shovel 100 to the remote operation support device 400 or the remote monitoring support device via the communication device 60 and display it on the remote operation support device 400 or the remote monitoring device. This allows the user to operate the shovel 100 or monitor the work of the shovel 100 while grasping the shape of the soil of the work target of the shovel 100 through the image representing the shape of the soil of the work target of the shovel 100 displayed on the display device 50A or the like. The display device 50A or the like can update the image representing the shape of the soil of the work target of the shovel 100 in accordance with the execution of the predetermined operation of the shovel 100. This allows the user to more appropriately operate the shovel 100 and monitor the work being performed by the shovel 100 while understanding the shape of the soil and sand that the shovel 100 is working on in real time.

In this way, in this example, the controller 30 more appropriately grasps the shape of the soil that is the target of work by the shovel 100 within the observation area, and as a result, the user can more appropriately grasp the shape of the soil that is the target of work through the display of an image representing the soil shape. Therefore, the user can more appropriately operate the shovel 100 and more appropriately monitor the work of the shovel 100 while grasping the shape of the soil that is the target of work.

When the shovel 100 is remotely operated, some or all of the functions of the learned model storage unit 302A, the work object shape acquisition unit 302B, and the display processing unit 302E may be provided in the remote operation support device 400. In addition, the function of the work object shape acquisition unit 302B may be transferred to the information processing device 200. This can reduce the processing load on the shovel 100.

[Specific example of processing by the work object shape acquisition unit]
Next, a specific example of the processing of the work object shape acquisition section 302B will be described with reference to FIGS.

In this example, the explanation will be given under the assumption that the specified operation of the shovel 100 is an excavation operation.

Figure 8 is a flow chart that shows an example of the processing of the work object shape acquisition unit 302B. Figure 9 is a diagram showing an example of the observation object area. Figure 10 is a diagram showing an example of the influence area.

The flowchart in FIG. 8 is executed, for example, after the excavation operation of the shovel 100 is performed. In the following, the explanation of this flowchart will be given on the premise that data is acquired that represents the shape of the work target (soil and sand shape) after the kth (k: positive integer) excavation operation of the shovel 100 is performed since the start of work.

For example, as shown in Fig. 9, an observation target area TA around the shovel 100 is divided into a predetermined number N of lattices. The observation target area TA is an area around the shovel 100 from which the work target shape acquisition unit 302B acquires data representing the shape of the soil. In this example, the soil height h _e ^k and the uncertainty s _e ^k corresponding to the estimation accuracy are acquired for each lattice i (i = 1 to N) of the observation target area TA as data representing the soil shape. The soil height h _e ^k and the uncertainty s _e ^k are expressed by the following equations (1) and (2).

In step S102, the work object shape acquisition unit 302B inputs data on the soil shape before the excavation operation of the shovel 100 is performed. The data on the soil shape before the excavation operation of the shovel 100 is equivalent to data on the soil shape after the (k-1)th excavation operation is performed (soil height h _e ^k-1 and uncertainty s _e ^k-1 ).

Furthermore, in the case of the first excavation operation (k=1), the work object shape acquisition unit 302B inputs the initial values of the soil shape data (soil height _he ⁰ and uncertainty s _e ⁰ ).

The initial value of the soil shape data may be obtained based on the output of the sensor 40 (shape sensor), may be obtained from outside the shovel 100, or may be a predefined assumed value. The predefined assumed value is, for example, zero (0) when it is assumed that the entire observation target area TA (all grids i) is at the same height as the ground at the position of the shovel 100.

When the processing of step S102 is completed, the work object shape acquisition unit 302B proceeds to step S104.

In step S104, the work object shape acquisition unit 302B inputs a log of the current excavation operation of the excavator 100 for each grid i in the observation target area TA. The log includes the height b ^k of the blade tip (toe) of the bucket 6, the angle φ ^k of the blade tip (toe) of the bucket 6, the excavation reaction force f ^k , the soil characteristic λ ^k , and the impact information κ ^k . The log may also include other information ω ^k .

The height ^bk of the blade tip of the bucket 6 means the height passed by the blade tip of the bucket 6 during the current excavation operation of the shovel 100 for each grid i in the observation area TA, and is expressed by the following equation (3).

The height ^bk of the blade edge of the bucket 6 does not need to be input for a grid i corresponding to a position where the bucket 6 has not passed, or an appropriate value may be input. The same applies to the angle φ ^k of the blade edge of the bucket 6 and the excavation reaction force f ^k described below. The height ^bk of the blade edge of the bucket 6 is acquired, for example, based on data on the trajectory of the bucket 6 during the current excavation operation of the shovel 100. The data on the trajectory of the bucket 6 is acquired, for example, based on time-series data of the outputs of the sensors S1 to S6 during the current excavation operation of the shovel 100.

The angle φ ^k of the blade tip of the bucket 6 means the angle of the blade tip of the bucket 6 with respect to a predetermined reference plane (e.g., a horizontal plane) when the blade tip of the bucket 6 passes through each grid i of the observation area TA during the current excavation operation of the shovel 100, and is expressed by the following equation (4).

The angle ^φk of the blade tip of the bucket 6 is acquired, for example, based on data of the trajectory of the bucket 6 during the current excavation operation of the shovel 100 and time-series data of the attitude angle of the bucket 6. The time-series data of the attitude angle of the bucket 6 is acquired, for example, based on time-series data of the output of the sensor S3 during the current excavation operation of the shovel 100.

The excavation reaction force f ^k means the reaction force acting from the ground to the bucket 6 during the current excavation operation of the shovel 100 for each grid i in the observation area TA, and is expressed by the following equation (5).

The excavation reaction force f ^k is acquired, for example, based on the time-series data of the outputs of the sensors S7 to S9 during the current excavation operation of the shovel 100.

The excavation reaction force for each grid point i may be expressed as a vector. In this case, the soil characteristic λ _i ^k for each grid point i in the observation target area TA is three-dimensional instead of one-dimensional.

The sediment characteristic λ ^k means the sediment characteristic for each grid i in the observation target area TA, and is expressed by the following equation (6).

The sediment characteristic λ ^k is, for example, the angle of repose for each grid i in the observation target area TA. The sediment characteristic λ ^k is, for example, specified in advance. The sediment characteristic λ ^k may also be obtained based on time series data of the output of the sensor 40 or the outputs of the sensors S7 to S9.

Note that there may be multiple types of sediment characteristics for each grid point i. In this case, the sediment characteristics λ _i ^k for each grid point i in the observation target area TA are multidimensional rather than one-dimensional.

The influence information κ ^k indicates whether or not the soil shape is directly influenced by the current excavation operation of the excavator 100 for each grid i of the observation target area TA. For example, the influence information κ ^k indicates whether or not the cutting edge of the bucket 6 passes through for each grid i of the observation target area TA, and is expressed by the following formula (7).

For example, if the blade tip of the bucket 6 passes through a grid i (i=1,...,N) in the observation area TA during the current excavation operation, and the height of the blade tip of the bucket 6 at that time is equal to or less than the height of the soil _he,i ^k-1 , the impact information κ _i ^k is set to "+1" (κ _i ^k = +1). On the other hand, if the blade tip of the bucket 6 does not pass through a grid i (i=1,...,N) in the observation area TA during the current excavation operation, or if the blade tip of the bucket 6 passes through a grid i (i=1,...,N) in the observation area TA but its height at that time is higher than the height of the soil _he,i ^k-1 , the impact information κ _i ^k is set to "-1" (κ _i ^k = -1).

The other information ω ^k includes, for example, the weight w ^k and volume v ^k of the soil contained in the bucket 6 after the shovel 100 has performed an excavation operation, and is expressed by the following equation (8).

When the processing of step S104 is completed, the work object shape acquisition unit 302B proceeds to step S106.

In step S106, the work object shape acquisition unit 302B updates the uncertainty s _e,i ^k−1 of the soil shape.

For example, the work object shape acquisition unit 302B sets an area (hereinafter, "influence area") Ω in which the soil shape (soil height h _e,i ^k ) is affected by the current excavation operation of the shovel 100. Then, the work object shape acquisition unit 302B determines that the uncertainty s _e,i ^k of the soil shape has increased for the grid i included in the influence area Ω, and updates it using the following formula (9).

For example, as shown in Fig. 10, the influence area Ω is set as a range obtained by expanding the excavation area EA by a predetermined amount in all directions. The excavation area EA is an area within the observation area TA that corresponds to a set of lattices i through which the blade tip of the bucket 6 passed during the current excavation operation of the shovel ¹⁰⁰ and whose height at that time was equal to or less than the height he _,i of the soil and sand.

The increment c _i of the uncertainty s _e,i ^k is, for example, the same value for each grid in the affected area Ω. In addition, the increment c _i of the uncertainty s _e,i ^k may be set so that it is largest in the excavation area EA in the affected area Ω and becomes smaller as it moves away from the excavation area EA.

When the processing of step S106 is completed, the work object shape acquisition unit 302B proceeds to step S108.

In step S108, the work object shape acquisition unit 302B identifies the shape of the soil before the excavator 100 performs the current excavation operation based on the output of the sensor 40. This allows the work object shape acquisition unit 302B to identify the shape of the soil after the excavator 100 performs the current excavation operation for the grid i in the observation target area TA where the sensor 40 was able to measure the soil height.

For example, the work object shape acquisition unit 302B applies a Kalman filter and corrects the shape of the soil after the previous excavation operation of the shovel 100 is performed based on the output of the sensor 40, thereby identifying the shape of the soil after the current excavation operation of the shovel 100 is performed.

When the Kalman filter is applied, when the soil height z _i is observed with variance s _i for any grid i in the observation area TA after the excavation operation of the shovel 100, the soil height h _e,i ^k and its uncertainty s _e,i ^k are expressed by the following equations (10) to (14).

Equations (10) to (14) can be summarized as function K, as shown below.

Therefore, for a grid i in the observation area TA, when the soil height z _l,i is measured by the sensor 40 with a variance s _l,i , the soil height h _l,i ^k and uncertainty s _l,i ^k based on the output of the sensor 40 are expressed by the following equation (16).

As a result, the work object shape acquisition unit 302B can acquire (identify) the soil height h _l,i ^k and uncertainty s _l,i ^k based on the output of the sensor 40 after the shovel 100 has performed the current excavation operation.

The height h _l ^k of soil for each grid point i in the observation target area TA, based on the output of the sensor 40, is expressed by the following equation (17).

The sensor 40 may not be able to measure the height of all the lattices i in the observation target area TA due to occlusion or the like. Therefore, the height of the sediment h _l,i ^k and the uncertainty s _l,i ^k are obtained by formula (16) only for the lattices i in which the height of the sediment could be measured by the sensor 40. The height of the sediment h _l,i ^k and the uncertainty s _l,i ^k for the lattices i in which the height of the sediment could not be measured by the sensor 40 are maintained at, for example, the previous values (height of the sediment h _l,i ^k-1 and uncertainty s _l,i ^k-1 ). In addition, the height of the sediment h _l,i ^k and the uncertainty s _l,i ^k for the lattices i in which the height of the sediment could not be measured by the sensor 40 may be designated as a value indicating that they are unknown ("unknown"). Hereinafter, the measurement feasibility information m _l ^k indicating whether or not the sensor 40 was able to measure the shape of the sediment for each lattice i in the observation target area TA is used. For example, the measurement feasibility information m _l ^k is expressed by the following equations (18) to (20).

When the processing of step S108 is completed, the work object shape acquisition unit 302B proceeds to step S110.

In step S110, the work object shape acquisition unit 302B uses a function g corresponding to the learned model LM1 to infer the soil shape (soil height z _p ^k and its uncertainty s _p ^k ) for each grid i.

The function g is, for example, mainly configured with a deep neural network (DNN). It is also possible to use U-Net with the input and output in the form of an image. In this case, the other information ω ^k in the above formula (8) does not take the form of an image, so it may be expanded into the form of an image, or may be directly input to the intermediate layer.

Then, similarly to step S108, the work object shape acquisition unit 302B applies a Kalman filter and estimates the shape of the soil after the current excavation operation of the shovel 100 is performed based on the inference result of the function g. For the grid i in the observation target area, the soil height h _p,i ^k and uncertainty s _p,i ^k based on the inference result of the function g are expressed by the following formula (22).

When processing of step S110 is completed, the work object shape acquisition unit 302B proceeds to step S112.

In step S112, the work object shape acquisition unit 302B generates data (height h e k and uncertainty s e k ) representing the final shape of the soil after the excavation operation of the shovel 100 is performed, based on the outputs of the processes in both steps ^S108 and _S110 . That is, the work object shape acquisition unit 302B integrates the data on the soil shape based on the output of the sensor 40, which is output in the process of step S108, and the data on ^the _soil shape based on the inference result of the function g, which is output in the process of step S110.

For example, the work object shape acquisition unit 302B treats the data of the soil shape (soil height h _l,i ^k and uncertainty s _l,i ^k ) identified based on the output of the sensor 40 in the processing of step S108 as the final data of the soil shape (soil height h _e,i ^k and uncertainty s _e,i ^k ).

However, as described above, due to occlusion of the sensor 40 or the like, there may be a lattice i where the shape of the soil is not identified based on the output of the sensor 40 in the processing of step S108, that is, a lattice i where the value of the measurement feasibility information m _l ^k is "-1." Therefore, for this lattice i, the work object shape acquisition unit 302B sets the data of the soil shape (soil height h _p,i ^k and uncertainty s _p,i ^k ) identified based on the result of the inference of the function g in the processing of step S110 as the final data of the soil shape.

In other words, the work object shape acquisition unit 302B generates the final soil shape data using the following equations (23) and (24).

In addition, for the grid i for which the sensor 40 has been able to measure the soil shape after the excavator 100 has performed the current excavation operation, the data on the soil shape identified based on the results of inference using the function g in the processing of step S110 may be used as the final soil shape data.

When processing of step S110 is completed, the work object shape acquisition unit 302B proceeds to step S112.

In step S112, the work object shape acquisition unit 302B outputs data on the soil shape (soil height h _e ^k and uncertainty s _e ^k ) generated in step S110.

As a result, for example, the target trajectory generating unit 302C can generate a target trajectory for the working part of the excavator 100, i.e., the bucket 6 (cutting edge), based on the soil shape data output from the work object shape acquiring unit 302B.

Further, for example, the display processing unit 302E can generate an image showing the shape of the soil in the observation target area TA around the shovel 100 based on the data of the soil shape output from the work target shape acquisition unit 302B. Therefore, the display processing unit 302E can display the image showing the soil shape in the observation target area TA around the shovel 100 on the display device 50A, or transmit it to the remote operation support device 400 or the remote monitoring support device via the communication device 60 and display it on these display devices. Furthermore, the display processing unit 302E may reflect the uncertainty s _e ^k in the image showing the shape of the soil in the observation target area TA around the shovel 100. For example, the display processing unit 302E expresses the uncertainty s _e ^k for each grid i in the observation target area TA around the shovel 100 by the color of the part corresponding to the grid i in the image showing the shape of the soil. This enables the display processing unit 302E to display an image showing the shape of the soil and sand in the observation area TA around the shovel 100 so that the difference in uncertainty for each grid i within the observation area TA around the shovel 100 can be recognized.

In addition, the work object shape acquisition unit 302B may output other data obtained in the process of the present flowchart in addition to the data on the soil shape. For example, the work object shape acquisition unit 302B may output measurement feasibility information m _l ^k . This allows the controller 30 to distinguish between the grid i in the observation target area TA in which the sensor 40 was able to measure the soil shape and the grid i in which the sensor 40 was unable to measure the soil shape. Therefore, for example, when displaying an image showing the soil shape in the observation target area TA on the display device 50A or the like, the display processing unit 302E can display the grid i in which the output of the sensor 40 is reflected and the grid in which the output of the sensor 40 is not reflected, in a distinguished manner.

When the processing of step S114 is completed, the work object shape acquisition unit 302B ends the processing of this flowchart.

In this way, in this example, the work object shape acquisition unit 302B can use the function g to estimate the soil shape after the excavation operation from the soil shape before the excavation operation is performed, taking into account the trajectory (track) of the bucket 6 during the excavation operation of the shovel 100, the excavation reaction force, the soil characteristics, etc.

In this example, even if the specified operation is an earth-discharging operation, the work object shape acquisition unit 302B can generate and output data on the earth-discharging shape of the excavator 100 by the same process as described above. In this case, for example, the other information ωk is expressed by the following formula (25).

As shown in formula (25), the other information ^ωk includes the weight Wk ^-1 and volume Vk-1 of the soil contained in the bucket 6 before the excavator 100 performs the soil discharge operation, and the weight ^Wk and volume ^Vk of the soil contained in the bucket 6 after the excavator ¹⁰⁰ performs the soil discharge operation. Also, as shown in formula (25), when the soil discharge destination is the bed of a truck, the other information ^ωk may include the positions ρ of the four sides of the bed of the truck in a plan view. This allows the work object shape acquisition unit 302B to estimate the soil shape of the bed taking into account the shape of the bed of the truck.

In addition, for work performed by a combination of excavation and soil discharge operations of the shovel 100, the work object shape acquisition unit 302B can generate and output data on the soil shape after the excavation or soil discharge operation of the shovel 100 by processing similar to that described above.

[Specific example of how to generate a trained model]
Next, a specific example of a method for generating the trained model LM1 will be described.

In this example, we explain how to generate a function g corresponding to the trained model LM1 used in the process of Figure 8 above.

The teacher data cj (j = 1 to L) of the teacher dataset D is expressed, for example, by the following equation (26).

The teacher data ^cj is ^a combination ^{of input data h^ej, s^ej} _{, hlj} ^{, slj} _, ^mlj , bj, ^{φj , fj} , ^λj , ^κj , _ωj and the ^height of _the soil _hrj ^after the excavation operation of the shovel 100 as correct data. The input data h^ _ej , s _^ ^ej , h ^{lj ,} s _lj , _m ^lj , _b ^j , φ ^j , f ^j , λ ^j , κ ^j , and ^{ω j correspond} to the input data (h _e ^k-1 , s _e ^k-1 , h _l ^k , s _{l k, m l} ^k _, ^{b k ,} φ ^k , f ^k , λ ^k , κ ^k , ω ^k ) of function g in equation (21).

As shown in the following equation (27), the function g has a parameter W, and machine learning is performed by optimizing the parameter W using the training data set D.

For example, the parameter W is optimized so that the loss function E(W) in the following equation (28) is minimized, and a function g corresponding to the trained model LM1 is generated.

As described above, the teacher dataset D may be generated from the log acquired by the log acquisition unit 2001, may be generated from the log acquired by the simulator unit 2002, or may be generated from both logs.

In the simulator unit 2002, for example, as described above, particle simulation such as DEM is adopted, and the height h _r ^j of the soil is obtained by ray tracing of a shape sensor such as a LIDAR that is virtually placed with respect to the position of the particle.

The teacher dataset D may also include a base teacher dataset generated from the log acquired by the simulator unit 2002, as described above, and a teacher dataset for fine tuning generated from the log acquired by the log acquisition unit 2001. In this case, the number of teacher data included in the teacher dataset for fine tuning may be relatively small.

In relation to the acquisition of the input data h _l ^j , S _l ^j , and m _l ^j , a part of the measurement data of the sensor group 300 or the measurement data of the virtual shape sensor arranged in the virtual space of the simulator unit 2002 may be virtually masked. As a result, even if occlusion does not occur in the sensor group 300 or the virtual shape sensor arranged in the virtual space of the simulator unit 2002, it is possible to acquire measurement data in which occlusion has virtually occurred. In addition, an occlusion area in the observation target area TA may be specifically calculated by ray tracing the shape sensor arranged in the virtual space of the simulator unit 2002. In addition, the occlusion area may be changed while changing the position of the shape sensor arranged in the virtual space of the simulator unit 2002. In this way, it is possible to realize robust machine learning for the function g.

^{In addition, the input data h^ej, s^ej} _{correspond to} the previous output (inference result) of the function g, and may be obtained by using multiple excavation operations repeated in time series. In addition, from the viewpoint ^of suppressing an increase in the number of data points, they may be substituted by learning while mixing a virtually large noise. This makes it possible to realize more robust machine learning for the function g.

In this way, the information processing device 200 can generate a teacher data set D including the teacher data ^cj , and generate a function g corresponding to the trained model LM1 by machine learning based on the teacher data set D.

[Action]
Next, the operations of the work machine, information processing device, and program according to this embodiment will be described.

In this embodiment, the work machine is equipped with a processing device. The work machine is, for example, the above-mentioned shovel 100. The processing device is, for example, the above-mentioned controller 30. Specifically, the processing device estimates the shape of the work target in accordance with the operation of the work machine.

In addition, in this embodiment, the information processing device may estimate the shape of the work target of the work machine according to the operation of the work machine. The information processing device is, for example, the above-mentioned controller 30, information processing device 200, or remote operation support device 400.

In addition, in this embodiment, the program may cause the information processing device to estimate the shape of the work target of the work machine based on the operation of the work machine.

This allows the work machine etc. to estimate the state of the work object by taking into account changes in the shape of the work object according to the operation of the work machine, for example. As a result, the work machine etc. can more appropriately grasp the shape of the work object.

In this embodiment, the work machine may also be equipped with a first acquisition device. The first acquisition device is, for example, the above-mentioned sensors S7 to S9. Specifically, the first acquisition device may acquire data related to the trajectory of the work part of the work machine. The processing device or information processing device may then estimate the shape of the work object based on the data related to the trajectory of the work part when a specified operation is performed.

This allows the work machine, etc. to estimate the state of the work object by taking into account changes in the shape of the work object from the trajectory of the work area and the positional relationship between the work area and the work object.

In this embodiment, the work machine may also be equipped with a measuring device. The measuring device is, for example, the sensor 40 described above. Specifically, the measuring device may measure the shape of a work object around the work machine. The processing device or information processing device may then estimate the shape of the work object based on the measurement data of the shape of the work object and data related to the trajectory of the work part when a specified operation is performed.

This allows a work machine or the like to estimate the shape of a work object, for example, starting from the shape of the work object at a certain point in time, and taking into account changes in the shape of the work object from the trajectory of the work area.

In addition, in this embodiment, the processing device or information processing device may estimate the shape of the work object after the specified operation is performed based on measurement data of the shape of the work object before the specified operation is performed, measurement data of the shape of the work object after the specified operation is performed, and data related to the trajectory of the work part when the specified operation is performed.

This allows the work machine, etc., to estimate the shape of the work object after the work machine has performed a specified operation, for example, based on the measurement data from the measuring device, and from the trajectory of the work area for areas that cannot be measured due to occlusion, etc.

In addition, in this embodiment, the processing device or information processing device may estimate the shape of the work object based on the characteristics of the soil to be worked on, or the soil to be added to the work object in response to the operation of the work machine.

This allows work machines, etc. to take into account the characteristics of the soil and sand and more accurately estimate the shape of the work target.

In addition, in this embodiment, the characteristics of the soil may include at least one of the angle of repose of the soil, the moisture content of the soil, and the grain size of the soil.

This allows work machines, etc. to more accurately estimate the shape of the work object by taking into account the angle of repose, moisture content, and grain size of the soil.

In this embodiment, the work machine may also be equipped with a second acquisition device. The second acquisition device is, for example, the sensors S7 to S9 described above. Specifically, the second acquisition device may acquire data related to the reaction force from the work object to the work part. The processing device or information processing device may then estimate the shape of the work object based on the data related to the reaction force to the work part when a specified operation is performed.

This allows the work machine etc. to, for example, recognize contact with underground rocks from the reaction force on the working part when the work machine is performing a specified operation, and to recognize characteristics such as the hardness of the soil. Therefore, the work machine etc. can take these recognition results into account and more appropriately estimate the shape of the work target.

In addition, in this embodiment, the processing device or information processing device may estimate the shape of the work object based on the estimated shape of the work object and measurement data of the shape of the work object obtained by the measuring device after the estimated shape is output.

This allows the processing device or information processing device to more appropriately estimate the shape of the work object by using the results of machine learning based on the difference between the estimated result of the shape of the work object and the measurement result of the measuring device after the estimated result is output.

In addition, in this embodiment, there may be multiple predetermined operations of the work machine. The processing device or information processing device may estimate the shape of the work target according to the predetermined operation performed by the work machine among the multiple predetermined operations.

This allows the work machine, etc. to estimate the state of the work target in accordance with the specified operation performed by the work machine.

In addition, in this embodiment, the working part of the work machine may be a bucket. And the specified operation of the work machine may be an excavation operation or an earth removal operation.

This allows the work machine, etc. to more appropriately estimate the shape of the soil being worked on, taking into account changes in the shape of the work object in response to the excavation and soil removal operations of the work machine.

In addition, in this embodiment, the work machine may be equipped with a control device that controls the operation of the work machine based on the estimated result of the shape of the work object. Furthermore, the information processing device may be equipped with a control unit that controls the operation of the work machine based on the estimated result of the shape of the work object.

This allows the work machine, etc. to control its operation according to the shape of the work object.

In addition, in this embodiment, the work machine may be equipped with a display device that displays the estimated results of the shape of the work target. The display device is, for example, the output device 50 described above.

In addition, in this embodiment, the program may cause the support device to estimate the shape of the work target of the work machine in accordance with the operation of the work machine and display the estimated shape of the work target. The support device is, for example, the remote operation support device 400.

This allows the work machine, etc. to present the estimated shape of the work object to the operator, etc.

In addition, in this embodiment, the work machine may be equipped with a display device that displays the estimated shape of the work object. The processing device or information processing device may estimate the shape of the work object in accordance with the operation of the work machine, and output the uncertainty of the estimated shape of the work object according to the position within the work object. The display device may then display the estimated shape of the work object so that the difference in uncertainty according to the position within the work object can be identified.

In addition, in this embodiment, the program may cause the support device to estimate the shape of the work object of the work machine in accordance with the operation of the work machine, and output the uncertainty of the estimated result of the shape of the work object depending on the position within the work object. The program may then cause the support device to display the estimated result of the shape of the work object so that the difference in uncertainty depending on the position within the work object can be identified.

This allows the work machine, etc., to make the user aware of the estimated results of the shape of the work object, while at the same time making the user aware of the difference in the uncertainty of the estimated results depending on the position within the observation range.

Although the embodiments have been described in detail above, the present disclosure is not limited to such specific embodiments, and various modifications and variations are possible within the scope of the gist of the invention as described in the claims.

1 Lower traveling body 3 Upper rotating body 4 Boom 5 Arm 6 Bucket 30 Controller 31 Hydraulic control valve 32 Shuttle valve 33 Hydraulic control valve 40 Sensor 40B Sensor 40F Sensor 40L Sensor 40R Sensor 50 Output device 50A Display device 52 Input device 60 Communication device 100 Shovel 150 Support device 200 Information processing device 300 Sensor group 300-1 to 300-M Sensor 301 Operation log providing unit 301A Operation log recording unit 301B Operation log storage unit 301C Operation log transmission unit 302 Work support unit 302A Learned model storage unit 302B Work object shape acquisition unit 302C Target trajectory generation unit 302D Operation control unit 302E Display processing unit 400 Remote operation support device 2001 Log acquisition unit 2002 Simulator unit 2003 Log storage unit 2004 Teacher data generation unit 2004A Teacher data generation unit 2004B Teacher data generation unit 2005 Machine learning unit 2005A Machine learning unit 2005B Machine learning unit 2006 Learned model storage unit 2007 Distribution unit AT Attachment EA Excavation areas LM1, LM2 Learned models S1 to S9 Sensor SYS Operation support system TA Observation target area Ω Affected area

Claims (16)

A processing device is provided for estimating the shape of a work target in accordance with the operation of the work machine.
Working machinery. A first acquisition device is provided for acquiring data relating to a trajectory of a working portion of a work machine,
The processing device estimates a shape of a work object based on data regarding a trajectory of the work part when a predetermined operation is performed.
2. The work machine of claim 1. A measuring device is provided for measuring the shape of a work target around the work machine,
The processing device estimates a shape of the work object based on measurement data of the shape of the work object and data related to a trajectory of the work part when the predetermined operation is performed.
3. A work machine according to claim 2. the processing device estimates the shape of the work object after the execution of the predetermined motion based on measurement data of the shape of the work object before the execution of the predetermined motion, measurement data of the shape of the work object after the execution of the predetermined motion, and data relating to a trajectory of the working part during the execution of the predetermined motion.
4. A work machine according to claim 3. The processing device estimates a shape of the work object based on characteristics of the soil of the work object or soil added to the work object in response to the operation of the work machine.
A work machine according to any one of claims 1 to 4. The characteristics include at least one of an angle of repose of the soil, a moisture content of the soil, and a grain size of the soil.
6. A work machine according to claim 5. a second acquisition device that acquires data on a reaction force from the work object to the work part;
the processing device estimates a shape of the work object based on data relating to a reaction force on the work part when the predetermined motion is performed;
A work machine according to any one of claims 2 to 4. the processing device estimates a shape of the work object based on an estimation result of the shape of the work object and measurement data of the shape of the work object acquired by the measuring device after output of the estimation result;
A work machine according to claim 3 or 4. The predetermined operation may be a plurality of operations.
the processing device estimates a shape of the work target in accordance with a predetermined operation executed by a work machine among the plurality of predetermined operations;
A work machine according to any one of claims 2 to 4. the working part is a bucket,
The predetermined operation is an excavation operation or an earth removal operation.
A work machine according to any one of claims 2 to 4. a control device that controls an operation of a work machine based on the estimation result of the shape of the work object;
A work machine according to any one of claims 1 to 4. A display device is provided for displaying an estimation result of the shape of the work object.
A work machine according to any one of claims 1 to 4. a display device that displays an estimation result of the shape of the work object;
the processing device estimates a shape of the work object in accordance with an operation of a work machine, and outputs an uncertainty of an estimation result of the shape of the work object according to a position within the work object;
the display device displays the estimation result of the shape of the work object so that a difference in the uncertainty according to a position within the work object can be identified.
A work machine according to any one of claims 1 to 4. A shape of a work target of the work machine is estimated according to an operation of the work machine.
Information processing device. In the information processing device,
A shape of a work target of the work machine is estimated according to an operation of the work machine.
program. Support equipment:
A shape of a work target of the work machine is estimated according to an operation of the work machine;
Displaying the estimated result of the shape of the work object;
program.

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