CN111941428B - Obstacle avoidance control method and device - Google Patents
Obstacle avoidance control method and device Download PDFInfo
- Publication number
- CN111941428B CN111941428B CN202010826141.4A CN202010826141A CN111941428B CN 111941428 B CN111941428 B CN 111941428B CN 202010826141 A CN202010826141 A CN 202010826141A CN 111941428 B CN111941428 B CN 111941428B
- Authority
- CN
- China
- Prior art keywords
- obstacle avoidance
- target
- target obstacle
- data
- obstacle
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 40
- 230000004927 fusion Effects 0.000 claims abstract description 49
- 230000004888 barrier function Effects 0.000 claims description 17
- 230000015654 memory Effects 0.000 description 21
- 238000010586 diagram Methods 0.000 description 10
- 230000006870 function Effects 0.000 description 8
- 238000004891 communication Methods 0.000 description 4
- 230000008569 process Effects 0.000 description 3
- 239000000463 material Substances 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 230000001413 cellular effect Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000013500 data storage Methods 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 230000005611 electricity Effects 0.000 description 1
- 238000009434 installation Methods 0.000 description 1
- 230000002452 interceptive effect Effects 0.000 description 1
- 230000003137 locomotive effect Effects 0.000 description 1
- 238000010295 mobile communication Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Images
Classifications
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1674—Programme controls characterised by safety, monitoring, diagnostic
- B25J9/1676—Avoiding collision or forbidden zones
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J19/00—Accessories fitted to manipulators, e.g. for monitoring, for viewing; Safety devices combined with or specially adapted for use in connection with manipulators
- B25J19/02—Sensing devices
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1656—Programme controls characterised by programming, planning systems for manipulators
- B25J9/1664—Programme controls characterised by programming, planning systems for manipulators characterised by motion, path, trajectory planning
- B25J9/1666—Avoiding collision or forbidden zones
Landscapes
- Engineering & Computer Science (AREA)
- Robotics (AREA)
- Mechanical Engineering (AREA)
- Traffic Control Systems (AREA)
Abstract
The application provides an obstacle avoidance control method and device, and the device comprises: the strategy switching module is used for generating an obstacle avoidance strategy switching instruction under the condition that the current working condition changes; the fusion control module is used for determining a target obstacle avoidance strategy corresponding to the current working condition under the condition of receiving an obstacle avoidance strategy switching instruction; determining a corresponding target obstacle avoidance sensor and a corresponding target obstacle avoidance sensor driving module according to the information of the target obstacle avoidance sensor, and sending an enabling signal of the target obstacle avoidance sensor and the information of a target obstacle avoidance area to the target obstacle avoidance sensor driving module; and the obstacle avoidance sensor driving module is used for enabling the obstacle avoidance sensor and driving the obstacle avoidance sensor to detect obstacle data according to the obstacle avoidance area information. The device can realize that the AGV of same model is at complicated changeable application scene work, satisfies the obstacle avoidance demand under the different operating modes.
Description
Technical Field
The application relates to the field of logistics, in particular to an obstacle avoidance control method and device.
Background
An Automated Guided Vehicle (AGV) is an Automated conveying device widely used in the industries of warehouse logistics, factory, retail and the like to replace manpower to improve efficiency. Generally, the AGV has the requirement of obstacle avoidance when running in various scenes, and the obstacle avoidance is also a necessary function of the traditional AGV.
The traditional AGV that is applied to electricity merchant storage commodity circulation keeps away the barrier and mainly relies on the laser safety radar who installs in the locomotive to keep away the barrier. In order to adapt to different situations, the laser safety radar is generally simply configured according to data and states such as vehicle types, channel widths, shelf widths, whether loads are carried or not and the like. Such a method proves to be relatively stable and reliable over time in relatively simple and ideal environments such as e-commerce warehouse logistics, unmanned factories. However, under the scenes with relatively complex obstacle avoidance requirements such as a man-machine mixed field, various goods shelf carrying and various robot-like mixed fields, the traditional obstacle avoidance scheme with a single laser radar installed on the vehicle head and simple configuration can hardly meet the requirements. In order to meet the relatively complex obstacle avoidance requirement, obstacle avoidance sensors are usually added, and how to configure multiple sensors for combined obstacle avoidance becomes a difficulty.
Disclosure of Invention
The embodiment of the application provides a method and a device for obstacle avoidance control, which aim to solve the problems in the related art, and the technical scheme is as follows:
in a first aspect, an embodiment of the present application provides an obstacle avoidance control device, where the device includes a policy switching module, a fusion control module, and a plurality of obstacle avoidance sensor driving modules, where each obstacle avoidance sensor driving module drives a corresponding obstacle avoidance sensor;
the strategy switching module is used for generating an obstacle avoidance strategy switching instruction under the condition that the current working condition changes;
the fusion control module is used for determining a target obstacle avoidance strategy corresponding to the current working condition under the condition of receiving an obstacle avoidance strategy switching instruction, wherein the target obstacle avoidance strategy comprises target obstacle avoidance area information and target obstacle avoidance sensor information corresponding to the current working condition; the fusion control module is also used for determining a corresponding target obstacle avoidance sensor and a corresponding target obstacle avoidance sensor driving module according to the information of the target obstacle avoidance sensor, and sending an enabling signal of the target obstacle avoidance sensor and the information of a target obstacle avoidance area to the target obstacle avoidance sensor driving module;
the target obstacle avoidance sensor driving module is used for enabling the target obstacle avoidance sensor and driving the target obstacle avoidance sensor to detect obstacle data according to the target obstacle avoidance area information.
In a second aspect, an embodiment of the present application provides an obstacle avoidance control method, where the method includes:
under the condition that the current working condition changes, determining a target obstacle avoidance strategy corresponding to the current working condition, wherein the target obstacle avoidance strategy comprises target obstacle avoidance area information and target obstacle avoidance sensor information corresponding to the current working condition;
enabling a target obstacle avoidance sensor corresponding to the target obstacle avoidance sensor information;
and driving the target obstacle avoidance sensor to detect obstacle data according to the information of the target obstacle avoidance area.
In a third aspect, an embodiment of the present application provides an obstacle avoidance control device, including:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor, so that the at least one processor can execute the obstacle avoidance control method of the embodiment of the application.
In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, where computer instructions are stored in the computer-readable storage medium, and when the computer instructions are executed by a processor, the obstacle avoidance control method according to the embodiment of the present application is implemented.
The advantages or beneficial effects in the above technical solution at least include: the AGV can work in complex and changeable application scenes and meet obstacle avoidance requirements under different working conditions.
The foregoing summary is provided for the purpose of description only and is not intended to be limiting in any way. In addition to the illustrative aspects, embodiments, and features described above, further aspects, embodiments, and features of the present application will be readily apparent by reference to the drawings and following detailed description.
Drawings
In the drawings, like reference numerals refer to the same or similar parts or elements throughout the several views unless otherwise specified. The figures are not necessarily to scale. It is appreciated that these drawings depict only some embodiments in accordance with the disclosure and are therefore not to be considered limiting of its scope.
Fig. 1 is a flowchart of an obstacle avoidance control method according to an embodiment of the present application;
fig. 2 is an exemplary diagram of an obstacle avoidance area according to an embodiment of the present application;
FIG. 3 is an exemplary graph of obstacle data according to an embodiment of the present application;
fig. 4 is a schematic diagram of an obstacle avoidance control device according to an embodiment of the present application;
FIG. 5 is a diagram illustrating an exemplary application of a policy switching module workflow;
FIG. 6 is a diagram of an exemplary application of a fusion module workflow;
FIG. 7 is a diagram of another example application of a fusion module workflow;
fig. 8 is a flowchart illustrating an operation of an obstacle avoidance control apparatus according to an embodiment of the present application;
fig. 9 is a schematic diagram of an obstacle avoidance control device according to an embodiment of the present application.
Detailed Description
In the following, only certain exemplary embodiments are briefly described. As those skilled in the art will recognize, the described embodiments may be modified in various different ways, all without departing from the spirit or scope of the present application. Accordingly, the drawings and description are to be regarded as illustrative in nature, and not as restrictive.
Fig. 1 shows a flowchart of an obstacle avoidance control method according to an embodiment of the present application. The obstacle avoidance control method can be applied to AGV vehicles. As shown in fig. 1, the obstacle avoidance control method may include:
step S101, under the condition that the current working condition changes, determining a Target obstacle avoidance strategy (Target Plot) corresponding to the current working condition.
A preset obstacle avoidance strategy Group (Plot Group) may be provided, where the preset obstacle avoidance strategy Group includes obstacle avoidance strategies corresponding to all working conditions. Each obstacle avoidance strategy respectively comprises obstacle avoidance area information and obstacle avoidance sensor information. The information of the obstacle avoidance sensor is the information of the obstacle avoidance sensor which is enabled by the current obstacle avoidance strategy; and the obstacle avoidance area information is the obstacle avoidance area information of the obstacle avoidance sensor which is enabled by the current obstacle avoidance strategy. The obstacle avoidance area information may be key boundary points of the obstacle avoidance area, and the obstacle avoidance area may be set based on the key boundary points. The information of the obstacle avoidance Sensor may be identification information of the obstacle avoidance Sensor, or an obstacle avoidance Sensor List (Sensor List) composed of identification information of a plurality of obstacle avoidance sensors. The target obstacle avoidance strategy is selected from an obstacle avoidance strategy group, and further comprises target obstacle avoidance area information and target obstacle avoidance sensor information corresponding to the current working condition. The target obstacle avoidance sensor is an obstacle avoidance sensor which needs to be enabled according to a target obstacle avoidance strategy, the target obstacle avoidance sensor information is enabling information of the target obstacle avoidance sensor, and the target obstacle avoidance area information is obstacle avoidance area information of the target obstacle avoidance sensor. The working conditions comprise working environments of the AGV, such as a man-machine mixed field area, a single-machine operation area or a two-dimensional code area.
In one embodiment, step S101 may include: acquiring an obstacle avoidance strategy group in an initialization stage; and under the condition that the current working condition changes, determining a target obstacle avoidance strategy corresponding to the current working condition from the obstacle avoidance strategy group.
And S102, enabling the target obstacle avoidance sensor corresponding to the information of the target obstacle avoidance sensor.
The AGV comprises an AGV body (comprising a chassis), a plurality of obstacle avoidance sensors, a laser radar sensor, a plurality of combined type and set positions, wherein the obstacle avoidance sensors can be respectively arranged at different positions of the AGV body (comprising the chassis), the obstacle avoidance sensors can be laser radar sensors, the plurality of obstacle avoidance sensors can be of the same type or the same type, or of different types, and can be configured according to practical application scenes. Furthermore, the corresponding obstacle avoidance sensor can be determined to serve as the target obstacle avoidance sensor according to the identification information of the target obstacle avoidance sensor, and therefore the target obstacle avoidance sensor can be enabled.
In one embodiment, step S102 may include: traversing each obstacle avoidance sensor according to the target obstacle avoidance sensor list to determine the obstacle avoidance sensors contained in the target obstacle avoidance sensor list as target obstacle avoidance sensors; and sending an enabling signal to the target obstacle avoidance sensor to enable (open) the target obstacle avoidance sensor.
Further, the obstacle avoidance control method may further include: traversing each obstacle avoidance sensor according to the target obstacle avoidance sensor list to determine that the obstacle avoidance sensors not included in the target obstacle avoidance sensor list are incapacitating obstacle avoidance sensors; and sending a disabling signal to the disabling obstacle avoidance sensor so as to disable (close) the disabling obstacle avoidance sensor.
And S103, driving the target obstacle avoidance sensor to detect obstacle data according to the target obstacle avoidance area information.
Specifically, a target obstacle avoidance area can be set according to target obstacle avoidance area points; and driving the target obstacle avoidance sensor to detect obstacle data in the target obstacle avoidance area.
In one example, the setting of the target obstacle avoidance area according to the target obstacle avoidance area point may include: and issuing any polygon (target obstacle avoidance area) formed by connecting target obstacle avoidance area points (such as 8 obstacle avoidance area points) to a target obstacle avoidance sensor, wherein the target obstacle avoidance sensor takes the area as a detection area of an obstacle and detects obstacle data entering the area. Fig. 2 is a diagram showing an example of the arrangement of the obstacle avoidance area. In this example, 8 obstacle avoidance area points are calculated by a vehicle coordinate system (northwest coordinate system) to obtain obstacle avoidance area edges, and thus an obstacle avoidance area is obtained.
In one implementation, the method of the embodiment of the present application may further include: acquiring barrier data from a plurality of target obstacle avoidance sensors; and determining target obstacle data according to the acquired obstacle data and a preset fusion rule.
For example: selecting the closest obstacle data from the first obstacle data and the second obstacle data as target obstacle data when the distance difference between the first obstacle data and the second obstacle data is larger than 5 cm; and selecting the obstacle data with the highest priority from the first obstacle data and the second obstacle data as the target obstacle data when the distance difference between the first obstacle data and the second obstacle data is not more than 5 cm.
That is, if the distance difference between any two obstacle data is greater than 5cm, the nearest obstacle data is believed. And if the distance difference between any two pieces of obstacle data is less than or equal to 5cm, the obstacle data with the highest priority is believed. And fusing the obstacle data of each obstacle avoidance sensor based on the fusion rule to output target obstacle data.
The obstacle data is unified into a polar coordinate system in which the x-axis of the vehicle coordinate system (north-west days) is the polar axis. Fig. 3 shows an example graph of obstacle data.
Generally, AGV equipment applied to e-commerce warehouse logistics and applied to factories has many differences in requirements, such as the requirement of obstacle avoidance. Even in the same factory scenario, the demands of different types of factories for AGV obstacle avoidance often vary greatly. For example, the obstacle avoidance requirements of an unmanned factory on the AGVs are often relatively simple and loose, and the obstacle avoidance requirements of the factory on the AGVs can be met as long as the AGVs are ensured to be stably avoided between each other and between the AGVs and fixed equipment. However, in the case of a factory with a man-machine mixed field, the obstacle avoidance of the AGVs needs to consider the obstacle avoidance between the AGVs and the moving personnel in addition to the obstacle avoidance between the AGVs and the equipment. The obstacle avoidance requirement in such a scenario is far more complicated than that in the former scenario.
The traditional scheme of single laser radar obstacle avoidance and simple working condition configuration installed on a vehicle head can hardly meet the complex obstacle avoidance requirements including a man-machine mixed field. Taking a scene of a man-machine mixed field as an example, two points which cannot be met are: firstly, traditional scheme keeps away that barrier sensor only has a single line laser radar, and the barrier can not be kept away above and below the scanning height of radar, and vehicle left side right side and rear side all do not have the barrier sensor of keeping away, and AGV keeps away the barrier ability when backing a car and rotatory very limited. And secondly, a plurality of different sub-regions such as a man-machine mixed field region, a single machine operation region, a storage region, a two-dimensional code region and the like generally exist in the complete operation region of the scene of the man-machine mixed field, and different obstacle avoidance requirements such as an obstacle avoidance range exist in the different sub-regions.
According to the obstacle avoidance control method, the AGV of the same model can work in complex and changeable application scenes, and obstacle avoidance requirements under different working conditions are met.
The embodiment of the application also provides an obstacle avoidance control device which can be used for realizing the obstacle avoidance control method. Fig. 4 is a block diagram showing the configuration of the obstacle avoidance control device.
As shown in fig. 4, the obstacle avoidance control device includes a policy switching module 100, a fusion control module 200, and a plurality of obstacle avoidance sensor driving modules 300, where each obstacle avoidance sensor driving module 300 drives a corresponding obstacle avoidance sensor 1, 2 … … N, respectively.
The obstacle avoidance sensor driving module 300 may communicate with the obstacle avoidance sensor hardware to complete the initialization, configuration, status query, obstacle data query, and other functions of the obstacle avoidance sensor hardware.
The fusion control module 200 may maintain the obstacle avoidance policy group issued by the policy switching module 100, and data of the state (enabled state or disabled state) of the corresponding obstacle avoidance sensor, the obstacle avoidance area, and the like. Meanwhile, the target obstacle avoidance strategy is executed in response to an obstacle avoidance strategy switching instruction issued by the strategy switching module 100, so as to reconfigure the obstacle avoidance sensor.
The policy switching module 100 may maintain the obstacle avoidance policies for different obstacle avoidance conditions, that is, the obstacle avoidance policy group, index the obstacle avoidance policies, and send the index to the fusion control module 200. When the current working condition changes and the obstacle avoidance strategy needs to be switched, an obstacle avoidance strategy switching instruction is sent to the fusion control module 200.
Specifically, the strategy switching module 100 is configured to generate an obstacle avoidance strategy switching instruction under the condition that the current working condition changes; the fusion control module 200 is configured to determine a target obstacle avoidance policy corresponding to a current working condition when receiving an obstacle avoidance policy switching instruction; the fusion control module 200 is further configured to determine a corresponding target obstacle avoidance sensor and a corresponding target obstacle avoidance sensor driving module 300 according to the information of the target obstacle avoidance sensor, and send an enable signal of the target obstacle avoidance sensor and the information of the target obstacle avoidance area to the target obstacle avoidance sensor driving module 300; the target obstacle avoidance sensor driving module 300 is configured to enable the target obstacle avoidance sensor, and drive the target obstacle avoidance sensor to detect obstacle data according to the target obstacle avoidance area information.
Each module of the obstacle avoidance control device according to the embodiment of the present application is described below.
Fig. 5 shows an exemplary diagram of the operation of the policy switching module 100. As shown in fig. 5, the policy switching module 100 issues an obstacle avoidance policy group to the fusion control module 200 in an initialization stage (e.g., a power-on stage of the AGV), where the obstacle avoidance policy group includes obstacle avoidance policies corresponding to respective operating conditions, and the obstacle avoidance policies include obstacle avoidance area information and obstacle avoidance sensor information. The strategy switching module 100, under the condition that the current working condition changes, corresponds the current working condition corresponding to the target obstacle avoidance strategy to the working conditions in the obstacle avoidance strategy group one by one, generates an obstacle avoidance strategy switching instruction, and sends the obstacle avoidance strategy switching instruction to the fusion control module 200. And under the condition that the signal of successful switching returned by the fusion control module 200 is not received, continuously issuing an obstacle avoidance strategy switching instruction to the fusion control module 200 until the signal of successful switching returned by the fusion control module 200 is received.
The fusion control module 200 plays a role in communicating up and down in the whole obstacle avoidance control method. The obstacle avoidance policy group and the obstacle avoidance policy switching command issued by the policy switching module 100 are received upward and controlled. Sending the obstacle avoidance area to the obstacle avoidance sensor driving module 300, and enabling the corresponding obstacle avoidance sensor through the obstacle avoidance sensor driving module 300; the obstacle data in the vehicle coordinate system is acquired from the obstacle avoidance sensor driving module 300, and is control. And the fusion function is to obtain the barrier data of each obstacle avoidance sensor under the target obstacle avoidance strategy and then fuse the barrier data according to a preset fusion rule so as to determine the target barrier data.
In one example, before the AGV starts to work (initialization phase), the fusion control module 200 receives the obstacle avoidance policy group issued by the policy switching module 100. After the AGV starts moving, the policy switching module 200 issues a target obstacle avoidance policy that is effective under the current working condition, and after the fusion control module 200 receives the target obstacle avoidance policy, the fusion control module switches the obstacle avoidance sensors corresponding to the target obstacle avoidance policy and the obstacle avoidance areas of the sensors according to the target obstacle avoidance policy until the next working condition is switched.
In one embodiment, the fusion control module 200 traverses each obstacle avoidance sensor according to the target obstacle avoidance sensor list to determine a target obstacle avoidance sensor and a disabled obstacle avoidance sensor; sending an enabling signal of the target obstacle avoidance sensor to a target obstacle avoidance sensor driving module; and sending a disable signal of the disable obstacle avoidance sensor to the disable obstacle avoidance sensor driving module, wherein the disable obstacle avoidance sensor driving module is an obstacle avoidance sensor driving module corresponding to the disable obstacle avoidance sensor.
In an example, as shown in fig. 6, the fusion control module 200 receives an obstacle avoidance policy group issued by the policy switching module 100, acquires a target obstacle avoidance sensor list from a target obstacle avoidance policy when receiving an obstacle avoidance policy switching instruction sent by the policy switching module 100, and then traverses each obstacle avoidance sensor according to the target obstacle avoidance sensor list; after the traversal is completed, a signal of successful switching is returned to the strategy switching module 100; when one traversed obstacle avoidance sensor is a target obstacle avoidance sensor, calling a driving interface of an obstacle avoidance sensor driving module corresponding to the obstacle avoidance sensor to enable the obstacle avoidance sensor, and calling the driving interface to send a target obstacle avoidance area; when a certain traversed obstacle avoidance sensor is not a target obstacle avoidance sensor (even if the obstacle avoidance sensor can be avoided), a driving interface of an obstacle avoidance sensor driving module corresponding to the obstacle avoidance sensor is called to disable the obstacle avoidance sensor.
In one example, the target obstacle avoidance sensor list includes identification information of each obstacle avoidance sensor and an enabling or disabling state corresponding to the identification information, and the fusion control module 200 enables or disables the obstacle avoidance sensor according to the enabling or disabling state of each obstacle avoidance sensor in the target obstacle avoidance sensor list when traversing the obstacle avoidance sensor. When the corresponding state of one obstacle avoidance sensor in the target obstacle avoidance sensor list is an enabling state, the obstacle avoidance sensor can be regarded as a target obstacle avoidance sensor; when the corresponding state of one obstacle avoidance sensor in the target obstacle avoidance sensor list is the incapability state, the obstacle avoidance sensor can be regarded as an incapability obstacle avoidance sensor.
In another example, the target obstacle avoidance sensor list includes identification information of the target obstacle avoidance sensors, that is, identification information of the obstacle avoidance sensors that need to be enabled, and when the fusion control module 200 traverses the obstacle avoidance sensors, it determines each obstacle avoidance sensor to be a target obstacle avoidance sensor or a disabled obstacle avoidance sensor according to the identification information in the target obstacle avoidance sensor list.
In an embodiment, the obstacle avoidance sensor driving module 300 is further configured to obtain obstacle data from the corresponding obstacle avoidance sensor and send the obstacle data to the fusion control module 200, and the fusion control module 200 is further configured to determine target obstacle data according to the received obstacle data and a preset fusion rule. The fusion rule is introduced in the above obstacle avoidance control method, and is not described herein again.
Fig. 7 shows an example in which the obstacle avoidance sensor driving module 300 outputs target obstacle data. The method comprises the steps that an obsK represents barrier data acquired from a current obstacle avoidance sensor, an obsNst represents nearest barrier data, an obsFst represents farthest barrier data, an obsHst represents barrier data with the highest priority, and an obsOut represents barrier data output after fusion, namely target barrier data.
Obstacle avoidance sensor drive module 300 includes three unified drive interfaces: the obstacle avoidance area is provided with an interface, a sensor disabling enabling interface and a sensor obstacle data acquisition interface.
The obstacle avoidance area setting interface is a general interface open to the fusion control module 200, and the interface calculates obstacle avoidance area points by using a vehicle coordinate system (a northwest sky coordinate system) in a unified manner so as to determine a target obstacle avoidance area. According to the difference of the installation position of the obstacle avoidance sensor and the sensor type, the coordinate system may need to be converted and then sent to the obstacle avoidance sensor.
The sensor enable disable interface is a unified enable (open) disable (close) interface to the converged control module 200. The unified sensor enable/disable interface enables the fusion control module 200 to open and close the obstacle avoidance sensor more conveniently according to the requirements of the target obstacle avoidance strategy.
The sensor obstacle avoidance data acquisition interface is a unified obstacle data acquisition interface facing the fusion control module 200. The coordinate system of the data of the interface is a polar coordinate system with the x-axis of the vehicle coordinate system (north-west days) as the polar axis.
Fig. 8 shows an example of implementing the above-mentioned obstacle avoidance control method based on the obstacle avoidance control device of the embodiment of the present application. The obstacle avoidance strategy group comprises obstacle avoidance strategies A and B … … X which respectively correspond to working conditions A and B … … X, target obstacle avoidance sensors (A, B, C) and (A, C) … … (M) which respectively correspond to obstacle avoidance area points (A0, B1, C3) and (A2, C0) … … (M0). T0 is the power-on stage of AGV, namely the initialization stage before the movement of AGV; t1 is a preparation movement stage for completing initialization and changing the current working condition to a working condition A, and the stage is switched to an obstacle avoidance strategy A; t2 is the movement phase when the AGV starts to move; t3 is the AGV movement completion, and the current working condition changes to the preparation movement stage of working condition B, and this stage is switched to obstacle avoidance strategy B.
According to the example, the obstacle avoidance control device can enable the AGV to flexibly switch the obstacle avoidance strategy according to the change of the working conditions, and further adapt to the obstacle avoidance requirements under different working conditions.
It should be noted that the modules and the architecture of the obstacle avoidance control device are only an example for implementing the obstacle avoidance control method in the embodiment of the present application, and are not limited thereto, and those skilled in the art may adjust and set the obstacle avoidance control method as needed.
Fig. 9 shows a block diagram of an obstacle avoidance control device according to an embodiment of the present application. As shown in fig. 9, the apparatus includes: a memory 901 and a processor 902, the memory 901 having stored therein instructions executable on the processor 902. The processor 902, when executing the instructions, implements any of the work generation methods in the embodiments described above. The number of the memory 901 and the processor 902 may be one or more. The apparatus is intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The terminal or server may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be examples only, and are not meant to limit implementations of the present application that are described and/or claimed herein.
The device may further include a communication interface 903, which is used for communicating with an external device to perform data interactive transmission. The various devices are interconnected using different buses and may be mounted on a common motherboard or in other manners as desired. The processor 902 may process instructions for execution within the terminal or server, including instructions stored in or on a memory to display graphical information of a GUI on an external input/output device (such as a display device coupled to an interface). In other embodiments, multiple processors and/or multiple buses may be used, along with multiple memories and multiple memories, as desired. Also, multiple terminals or servers may be connected, with each device providing portions of the necessary operations (e.g., as an array of servers, a group of blade servers, or a multi-processor system). The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown in FIG. 9, but this does not indicate only one bus or one type of bus.
Optionally, in a specific implementation, if the memory 901, the processor 902, and the communication interface 903 are integrated on a chip, the memory 901, the processor 902, and the communication interface 903 may complete mutual communication through an internal interface.
It should be understood that the processor may be a Central Processing Unit (CPU), other general purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. A general purpose processor may be a microprocessor or any conventional processor or the like. It is noted that the processor may be an advanced reduced instruction set machine (ARM) architecture supported processor.
Embodiments of the present application provide a computer-readable storage medium (such as the above-mentioned memory 901), which stores computer instructions, and when executed by a processor, the program implements the method provided in the embodiments of the present application.
Alternatively, the memory 901 may include a program storage area and a data storage area, wherein the program storage area may store an operating system and an application program required by at least one function; the storage data area may store data created according to the use of a terminal or a server, and the like. Further, the memory 901 may include high speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, the memory 901 may optionally include memory located remotely from the processor 902, which may be connected to a terminal or server over a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
Wherein, the processor 902 may be a first processor or a second processor; the memory 901 may be a first memory or a second memory.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the application. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present application, "a plurality" means two or more unless specifically limited otherwise.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more (two or more) executable instructions for implementing specific logical functions or steps in the process. And the scope of the preferred embodiments of the present application includes other implementations in which functions may be performed out of the order shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved.
The logic and/or steps represented in the flowcharts or otherwise described herein, e.g., an ordered listing of executable instructions that can be considered to implement logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions.
It should be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. All or part of the steps of the method of the above embodiments may be implemented by hardware that is configured to be instructed to perform the relevant steps by a program, which may be stored in a computer-readable storage medium, and which, when executed, includes one or a combination of the steps of the method embodiments.
In addition, functional units in the embodiments of the present application may be integrated into one processing module, or each unit may exist alone physically, or two or more units are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. The integrated module may also be stored in a computer-readable storage medium if it is implemented in the form of a software functional module and sold or used as a separate product. The storage medium may be a read-only memory, a magnetic or optical disk, or the like.
The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive various changes or substitutions within the technical scope of the present application, and these should be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (13)
1. An obstacle avoidance control device is characterized by comprising a strategy switching module, a fusion control module and a plurality of obstacle avoidance sensor driving modules, wherein each obstacle avoidance sensor driving module drives a corresponding obstacle avoidance sensor;
the strategy switching module is used for generating an obstacle avoidance strategy switching instruction under the condition that the current working condition changes; the working condition comprises the working environment of the AGV;
the fusion control module is used for determining a target obstacle avoidance strategy corresponding to the current working condition under the condition of receiving the obstacle avoidance strategy switching instruction, wherein the target obstacle avoidance strategy comprises target obstacle avoidance area information and target obstacle avoidance sensor information corresponding to the current working condition; the fusion control module is further used for determining a corresponding target obstacle avoidance sensor and a corresponding target obstacle avoidance sensor driving module according to the information of the target obstacle avoidance sensor, and sending an enabling signal of the target obstacle avoidance sensor and the information of the target obstacle avoidance area to the target obstacle avoidance sensor driving module;
the target obstacle avoidance sensor driving module is used for enabling the target obstacle avoidance sensor and driving the target obstacle avoidance sensor to detect obstacle data according to the target obstacle avoidance area information.
2. The device according to claim 1, wherein the strategy switching module is further configured to issue an obstacle avoidance strategy group to the fusion control module in an initialization stage, where the obstacle avoidance strategy group includes obstacle avoidance strategies corresponding to each operating condition, and the obstacle avoidance strategies include obstacle avoidance area information and obstacle avoidance sensor information; and the fusion control module is further used for determining a target obstacle avoidance strategy corresponding to the current working condition from the obstacle avoidance strategy group according to the obstacle avoidance strategy switching instruction.
3. The apparatus of claim 1, wherein the target obstacle avoidance sensor information comprises a list of target obstacle avoidance sensors, the fusion control module further configured to: traversing each obstacle avoidance sensor according to the target obstacle avoidance sensor list to determine the target obstacle avoidance sensors and/or the incapability obstacle avoidance sensors; sending an enabling signal of a target obstacle avoidance sensor to the target obstacle avoidance sensor driving module; and/or sending a disabling signal of the disabling obstacle avoidance sensor to a disabling obstacle avoidance sensor driving module, wherein the disabling obstacle avoidance sensor driving module is an obstacle avoidance sensor driving module corresponding to the disabling obstacle avoidance sensor.
4. The device according to claim 1, wherein the target obstacle avoidance area information includes target obstacle avoidance area points, and the target obstacle avoidance sensor driving module is further configured to set a target obstacle avoidance area according to the target obstacle avoidance area points, and drive the target obstacle avoidance sensor to detect obstacle data in the target obstacle avoidance area.
5. The device according to claim 1, wherein each obstacle avoidance sensor driving module is further configured to acquire obstacle data from a corresponding obstacle avoidance sensor and send the obstacle data to the fusion control module, and the fusion control module is further configured to determine target obstacle data according to the received obstacle data and a preset fusion rule.
6. The apparatus of claim 5, wherein the fusion rule comprises:
selecting obstacle data closest to a first obstacle data and a second obstacle data as the target obstacle data when a distance difference between the first obstacle data and the second obstacle data is larger than 5 cm;
selecting, as the target obstacle data, obstacle data having the highest priority from among the first obstacle data and the second obstacle data, when a difference in distance between the first obstacle data and the second obstacle data is not more than 5 cm.
7. An obstacle avoidance control method is characterized by comprising the following steps:
determining a target obstacle avoidance strategy corresponding to the current working condition under the condition that the current working condition changes, wherein the target obstacle avoidance strategy comprises target obstacle avoidance area information and target obstacle avoidance sensor information corresponding to the current working condition; the working condition comprises the working environment of the AGV;
enabling a target obstacle avoidance sensor corresponding to the target obstacle avoidance sensor information;
and driving the target obstacle avoidance sensor to detect obstacle data according to the target obstacle avoidance area information.
8. The method of claim 7, wherein determining the target obstacle avoidance strategy corresponding to the current operating condition when the current operating condition changes comprises:
acquiring an obstacle avoidance strategy group in an initialization stage, wherein the obstacle avoidance strategy group comprises obstacle avoidance strategies corresponding to all working conditions respectively, and the obstacle avoidance strategies comprise obstacle avoidance area information and obstacle avoidance sensor information;
and under the condition that the current working condition changes, determining a target obstacle avoidance strategy corresponding to the current working condition from the obstacle avoidance strategy group.
9. The method of claim 7, wherein the target obstacle avoidance sensor information comprises a list of target obstacle avoidance sensors, enabling a target obstacle avoidance sensor corresponding to the target obstacle avoidance sensor information, comprising:
traversing each obstacle avoidance sensor according to the target obstacle avoidance sensor list to determine that an obstacle avoidance sensor included in the target obstacle avoidance sensor list is the target obstacle avoidance sensor;
and sending an enabling signal to the target obstacle avoidance sensor.
10. The method of claim 9, further comprising:
traversing each obstacle avoidance sensor according to the target obstacle avoidance sensor list to determine that the obstacle avoidance sensors not included in the target obstacle avoidance sensor list are incapacitating obstacle avoidance sensors;
and sending a disabling signal to the disabling obstacle avoidance sensor.
11. The method according to claim 7, wherein the target obstacle avoidance area information includes target obstacle avoidance area points, and driving the target obstacle avoidance sensor to detect obstacle data according to the target obstacle avoidance area information includes:
setting a target obstacle avoidance area according to the target obstacle avoidance area points;
and driving the target obstacle avoidance sensor to detect obstacle data in the target obstacle avoidance area.
12. The method of claim 7, further comprising:
acquiring barrier data from a plurality of target obstacle avoidance sensors;
and determining target obstacle data according to the acquired obstacle data and a preset fusion rule.
13. The method according to claim 12, wherein determining target obstacle data according to the acquired obstacle data and a preset fusion rule comprises:
selecting obstacle data closest to a first obstacle data and a second obstacle data as the target obstacle data when a distance difference between the first obstacle data and the second obstacle data is larger than 5 cm;
selecting, as the target obstacle data, obstacle data having the highest priority from among the first obstacle data and the second obstacle data, when a difference in distance between the first obstacle data and the second obstacle data is not more than 5 cm.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010826141.4A CN111941428B (en) | 2020-08-17 | 2020-08-17 | Obstacle avoidance control method and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010826141.4A CN111941428B (en) | 2020-08-17 | 2020-08-17 | Obstacle avoidance control method and device |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111941428A CN111941428A (en) | 2020-11-17 |
| CN111941428B true CN111941428B (en) | 2022-01-18 |
Family
ID=73342597
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010826141.4A Active CN111941428B (en) | 2020-08-17 | 2020-08-17 | Obstacle avoidance control method and device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111941428B (en) |
Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105487536A (en) * | 2014-10-13 | 2016-04-13 | 北京自动化控制设备研究所 | Low-cost autonomous obstacle avoidance method for mobile robot |
| CN106324619A (en) * | 2016-10-28 | 2017-01-11 | 武汉大学 | Automatic obstacle avoiding method of substation inspection robot |
| CN106363668A (en) * | 2016-10-08 | 2017-02-01 | 浙江国自机器人技术有限公司 | Dynamic detection safety protection method of mobile robot |
| CN109508004A (en) * | 2018-12-10 | 2019-03-22 | 鄂尔多斯市普渡科技有限公司 | A kind of barrier priority level avoidance system and method for pilotless automobile |
| CN109808686A (en) * | 2019-04-02 | 2019-05-28 | 上海快仓智能科技有限公司 | Vehicle obstacle-avoidance method, apparatus and vehicle |
| CN109901583A (en) * | 2019-03-21 | 2019-06-18 | 创泽智能机器人股份有限公司 | A kind of robot barrier analyte detection and path adjust system |
| CN110032183A (en) * | 2018-03-19 | 2019-07-19 | 徐州艾奇机器人科技有限公司 | A kind of round-the-clock unmanned cruiser system of four-wheel drive |
| CN110244708A (en) * | 2019-05-16 | 2019-09-17 | 芜湖智久机器人有限公司 | A kind of AGV vehicle obstacle avoidance system and method |
| KR20200064522A (en) * | 2018-11-29 | 2020-06-08 | (주)한림중공업 | Method for determination a priority of multiple obstacles to be avoided |
Family Cites Families (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104076817A (en) * | 2014-06-18 | 2014-10-01 | 北京计算机技术及应用研究所 | High-definition video aerial photography multimode sensor self-outer-sensing intelligent navigation system and method |
| US9630319B2 (en) * | 2015-03-18 | 2017-04-25 | Irobot Corporation | Localization and mapping using physical features |
| WO2018010024A1 (en) * | 2016-07-12 | 2018-01-18 | Braze Mobility Inc. | System, device and method for mobile device environment sensing and user feedback |
| CN106313086B (en) * | 2016-08-21 | 2018-07-06 | 西安科技大学 | A kind of coalmine rescue robot remote control system and control method |
| DE202018006349U1 (en) * | 2017-11-14 | 2020-02-21 | Positec Power Tools (Suzhou) Co., Ltd | Self-moving system |
-
2020
- 2020-08-17 CN CN202010826141.4A patent/CN111941428B/en active Active
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105487536A (en) * | 2014-10-13 | 2016-04-13 | 北京自动化控制设备研究所 | Low-cost autonomous obstacle avoidance method for mobile robot |
| CN106363668A (en) * | 2016-10-08 | 2017-02-01 | 浙江国自机器人技术有限公司 | Dynamic detection safety protection method of mobile robot |
| CN106324619A (en) * | 2016-10-28 | 2017-01-11 | 武汉大学 | Automatic obstacle avoiding method of substation inspection robot |
| CN110032183A (en) * | 2018-03-19 | 2019-07-19 | 徐州艾奇机器人科技有限公司 | A kind of round-the-clock unmanned cruiser system of four-wheel drive |
| KR20200064522A (en) * | 2018-11-29 | 2020-06-08 | (주)한림중공업 | Method for determination a priority of multiple obstacles to be avoided |
| CN109508004A (en) * | 2018-12-10 | 2019-03-22 | 鄂尔多斯市普渡科技有限公司 | A kind of barrier priority level avoidance system and method for pilotless automobile |
| CN109901583A (en) * | 2019-03-21 | 2019-06-18 | 创泽智能机器人股份有限公司 | A kind of robot barrier analyte detection and path adjust system |
| CN109808686A (en) * | 2019-04-02 | 2019-05-28 | 上海快仓智能科技有限公司 | Vehicle obstacle-avoidance method, apparatus and vehicle |
| CN110244708A (en) * | 2019-05-16 | 2019-09-17 | 芜湖智久机器人有限公司 | A kind of AGV vehicle obstacle avoidance system and method |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111941428A (en) | 2020-11-17 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110936383B (en) | Obstacle avoiding method, medium, terminal and device for robot | |
| EP4129581A1 (en) | Robot motion planning for avoiding collision with moving obstacles | |
| US8948913B2 (en) | Method and apparatus for navigating robot | |
| US20190317218A1 (en) | Ground environment detection method and apparatus | |
| CN109901578B (en) | Method and device for controlling multiple robots and terminal equipment | |
| EP3760505A1 (en) | Method and apparatus for avoidance control of vehicle, electronic device and storage medium | |
| US11275387B2 (en) | Coach apparatus and cooperative operation controlling method for coach-driven multi-robot-cooperative operation system | |
| CN111452042B (en) | Control method and system of mechanical arm and control terminal | |
| CN109048909B (en) | Branch node type path scheduling method and device, background server and first robot | |
| WO2022267283A1 (en) | Robot, navigation method and apparatus therefor, and computer-readable storage medium | |
| CN110715655A (en) | AGV positioning method, device and system based on real-time map updating | |
| CN111941428B (en) | Obstacle avoidance control method and device | |
| CN115638800A (en) | Cost map generation method and device, computer equipment and storage medium | |
| CN115269254A (en) | Order abnormity determining method, device, equipment and medium | |
| US20230221432A1 (en) | Sensor recognition integration device | |
| CN114489060A (en) | Unmanned ship formation control method, terminal device and computer-readable storage medium | |
| CN113627646A (en) | Path planning method, device, equipment and medium based on neural network | |
| JP6463567B1 (en) | Control planning apparatus, robot group system, and control planning method | |
| Wodtko et al. | Adaptive patched grid mapping | |
| CN112797983A (en) | Path planning method and device, unmanned equipment and storage medium | |
| CN117575452B (en) | Path planning method, device, equipment and medium based on node dynamic addressing | |
| CN111443700A (en) | Robot and navigation control method and device thereof | |
| CN116659538B (en) | Road diameter changing planning method and device and vehicle-mounted equipment | |
| Metelli | A unified view of configurable Markov Decision Processes: Solution concepts, value functions, and operators | |
| CN114035580B (en) | AGV control method, AGV control device, storage medium, processor and AGV equipment |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| CP03 | Change of name, title or address |
Address after: No. 210-69 Yangmuqiao, Huangxiang Street, Liangxi District, Wuxi City, Jiangsu Province Patentee after: Wuxi Kuaicang Intelligent Technology Co.,Ltd. Country or region after: China Address before: Room 1030, Zone B, Room 1205, No. 968 Memorial Road, Baoshan District, Shanghai Patentee before: SHANGHAI QUICKTRON INTELLIGENT TECHNOLOGY Co.,Ltd. Country or region before: China |