TWI821024B - System and method for controlling autonomous mobile robot - Google Patents

Abstract

A system and a method for controlling autonomous mobile robot are provided. An autonomous mobile robot wirelessly transmits sensing data to a local server device. The local server device uses the sensing data to perform a positioning operation and a navigation operation of the autonomous mobile robot, and generates and wirelessly transmits a navigation control command. The autonomous mobile robot receives the navigation control command from the local server device, and moves according to the navigation control command. The local server device provides actual state information of the autonomous mobile robot to the cloud server device. The cloud server device simulates virtual state information of the autonomous mobile robot according to a robot mathematical model of the autonomous mobile robot. When the actual state information does not match the virtual state information, the cloud server device performs a navigation correction operation.

Description

Autonomous mobile robot control system and method

The present invention relates to a robot control method, and in particular, to an autonomous mobile robot control system and method.

With the advancement of technology, Automated Guided Vehicles (AGVs) have gradually evolved into autonomous mobile robots (Autonomous Mobile Robots, AMRs) that are flexible, flexible, and capable of independent navigation. The biggest difference between the two is that automated guided vehicles require rails, magnetic strips, reflective strips and other objects to assist the vehicle in moving on fixed routes, but autonomous mobile robots use various sensing technologies and machine vision to achieve autonomous navigation. . It can be seen that the characteristics of autonomous mobile robots are that they are not only maneuverable and independent, but also can significantly reduce the construction cost of fixed devices such as tracks, magnetic tracks or conveyor belts. For example, autonomous mobile robots can transport goods or materials in warehouse centers or manufacturing plants. With the increasing handling demand and the possibility of labor shortage in the manufacturing and logistics industries, the application of autonomous mobile robots can not only ensure that factories or logistics The center's production and shipment are successfully completed, which can effectively improve manufacturing or transportation efficiency.

Currently, the positioning and navigation calculations of autonomous mobile robots are generally performed by the computer device of the autonomous mobile robot. However, due to the high computational complexity and large amount of calculations involved in positioning and navigation operations, the hardware specification requirements for autonomous mobile robots are also relatively high. If the hardware computing capability of the autonomous mobile robot is not ideal, the positioning and navigation calculations of the autonomous mobile robot may not be completed immediately, and thus the autonomous navigation of the autonomous mobile robot cannot be realized. Therefore, when a large number of autonomous mobile robots are deployed in the workplace, if the hardware cost of each autonomous mobile robot is very high, the overall deployment cost will be very high and does not meet the actual needs. In addition, there may be various unpredictable factors in the working field of autonomous mobile robots. These factors will affect the stability of autonomous navigation of autonomous mobile robots, and even prevent autonomous mobile robots from successfully completing tasks.

In view of this, the present invention proposes an autonomous mobile robot control system and method, which can solve the above technical problems.

Embodiments of the present invention provide an autonomous mobile robot control system, which includes a cloud server device, a local server device, and at least one autonomous mobile robot. The local server device can communicatively connect to the cloud server device. At least one autonomous mobile robot is wirelessly connected to the local server device and wirelessly transmits sensing data to the local server device. The local server device uses the sensing data to perform positioning operations and navigation operations of at least one autonomous mobile robot, and generates and wirelessly transmits navigation control instruction. At least one autonomous mobile robot receives navigation control instructions from the local server device and moves according to the navigation control instructions. The local server device provides actual status information of at least one autonomous mobile robot to the cloud server device. The cloud server device simulates the virtual state information of at least one autonomous mobile robot based on the robot mathematical model of the at least one autonomous mobile robot. When the actual status information does not match the virtual status information, the cloud server device performs a navigation correction operation.

Embodiments of the present invention provide an autonomous mobile robot control method, which is suitable for autonomous mobile robot control systems. The autonomous mobile robot control system includes a cloud server device, a local server device, and at least one autonomous mobile robot. The method includes the following steps. The sensing data is wirelessly transmitted to the local server device through at least one autonomous mobile robot. The sensing data is used to perform the positioning operation and navigation operation of at least one autonomous mobile robot through the local server device, and the navigation control instructions are generated and wirelessly transmitted through the local server device. Navigation control instructions are received from the local server device through at least one autonomous mobile robot, and the robot moves according to the navigation control instructions. Provide actual status information of at least one autonomous mobile robot to the cloud server device through the local server device. The virtual state information of at least one autonomous mobile robot is simulated through the cloud server device according to the robot mathematical model of the at least one autonomous mobile robot. When the actual status information does not match the virtual status information, the navigation correction operation is performed through the cloud server device.

Based on the above, in embodiments of the present invention, the local server device can perform the positioning operation and navigation operation of the autonomous mobile robot according to the sensing data provided by the autonomous mobile robot, and the autonomous mobile robot can receive guidance from the local server device. Navigation control instructions to move. Based on this, the computing hardware of autonomous mobile robots does not need to be responsible for huge and complex positioning and navigation operations, thereby significantly reducing the cost of deploying multiple autonomous mobile robots. In addition, during the movement of the autonomous mobile robot, the actual status information of the autonomous mobile robot can be provided to the cloud server device through the local server device, and the cloud server device can use the robot mathematical model to simulate the virtual status information of the autonomous mobile robot. The cloud server device can compare the actual status information with the virtual status information to decide whether to perform the navigation correction operation. Based on this, when the autonomous mobile robot encounters unexpected factors and fails to operate as expected, the cloud server device can assist the autonomous mobile robot to resume normal operation as soon as possible through navigation correction operations, thereby effectively improving the stability and reliability of the autonomous mobile robot.

10:Autonomous mobile robot control system

110:Cloud server installation

120:Local server device

130:Autonomous mobile robot

111,121,131:Storage device

112,122:Network module

113,123,133: Processor

124,134: Wireless communication module

N1:Internet

132: Sensor

135:Mobile device

1211: Positioning module

1212:Navigation module

1213:Map module

1214:Management module

1111:Smart decision-making module

1112: Running state simulation module

1113:Map management module

1114: Actual status information management module

S210~S260, S410~S490, S510~S590, S602~S620: steps

Figure 1 is a schematic diagram of an autonomous mobile robot control system according to an embodiment of the present invention.

Figure 2 is a flow chart of an autonomous mobile robot control method according to an embodiment of the present invention.

FIG. 3A is a schematic diagram of a software function module of a local server device according to an embodiment of the present invention.

FIG. 3B is a schematic diagram of a software function module of a local server device according to an embodiment of the present invention.

Figure 4 is a flow chart of an autonomous mobile robot control method according to an embodiment of the present invention. Process map.

Figure 5 is a flow chart of an autonomous mobile robot control method according to an embodiment of the present invention.

Figure 6 is a flow chart of an autonomous mobile robot control method according to an embodiment of the present invention.

Some embodiments of the present invention will be described in detail with reference to the accompanying drawings. The component symbols cited in the following description will be regarded as the same or similar components when the same component symbols appear in different drawings. These embodiments are only part of the present invention and do not disclose all possible implementations of the present invention. Rather, these embodiments are merely examples of methods and systems within the scope of the patent application of the present invention.

Figure 1 is a schematic diagram of an autonomous mobile robot control system according to an embodiment of the present invention. Referring to FIG. 1 , the autonomous mobile robot control system 10 includes a cloud server device 110 , a local server device 120 , and at least one autonomous mobile robot 130 . It should be noted that although FIG. 1 shows three autonomous mobile robots 130, the number of autonomous mobile robots is not limited in the present invention and can be set according to actual needs.

The cloud server device 110 is an electronic device with computing capabilities and networking capabilities. The cloud server device 110 may include (but is not limited to) a storage device 111, a network module 112, and a processor 113. The processor 113 can access and execute instructions, modules or programs in the storage device 111 to execute the autonomous mobile machine described in this disclosure. One or more operations of a human control method.

In some embodiments, the cloud server device 110 can be implemented by one or more cloud machines of a cloud computing platform. The cloud computing platform can be any cloud computing platform known in the art, such as Amazon Web Services (Amazon Web Services). Services, AWS), Microsoft Azure, GOOGLE CLOUD or other cloud computing platforms. The cloud server device 110 can utilize the network module 112 to connect to the network N1 to realize data transmission through the network N1. Network module 112 may include a wired transceiver or a wireless transceiver.

The local server device 120 is an electronic device with computing capabilities and networking capabilities. The local server device 120 may include (but is not limited to) a storage device 121, a network module 122, a processor 123, and a wireless communication module 124. The processor 123 can access and execute instructions, modules or programs in the storage device 121 to perform one or more operations of the autonomous mobile robot control method described in this disclosure.

In some embodiments, the local server device 120 may utilize the network module 122 to connect to the network N1 to implement data transmission through the network N1. Network module 122 may include a wired transceiver or a wireless transceiver. In other words, the local server device 120 can be communicatively connected to the cloud server device 110 via the network N1. Network N1 may include any of a variety of wireless and/or wired networks. For example, network N1 may include any combination of public and/or private networks, local area networks, and/or wide area networks, etc. Additionally, network N1 may utilize one or more wired and/or wireless communication technologies. In some embodiments, network N1 may include, for example, a cellular or other mobile network, a wireless local area network (WLAN), a wireless wide area network (WWAN), and/or the Internet. For example, the network N1 may include a Long Term Evolution (LTE) wireless network, a fifth generation (5G) wireless network (also known as a new radio (NR) wireless network or a 5G NR wireless network), Wi-Fi Fi WLAN or Internet.

In some embodiments, the wireless communication module 124 may include an antenna and a wireless transceiver to implement wireless data transmission. It should be noted that in different embodiments, the wireless communication module 124 and the network module 112 may be the same or different communication components. The local server device 120 can use the wireless communication module 124 to receive data from the autonomous mobile robot 130 and can use the wireless communication module 124 to transmit data to the autonomous mobile robot 130 .

The autonomous mobile robot 130 can move in the working environment, and it can be any form of autonomous mobile robot, such as a low-voltage autonomous mobile robot, a forklift-type autonomous mobile robot, or a trailer-type autonomous mobile robot, etc. The autonomous mobile robot 130 may include (but is not limited to) a storage device 131, a sensor 132, a processor 133, a wireless communication module 134, and a mobile device 135. The processor 133 can access and execute instructions, modules or programs in the storage device 131 to perform one or more operations of the autonomous mobile robot control method described in this disclosure.

In some embodiments, the sensor 132 may include an inertial sensor (such as an acceleration sensor, a gyroscope or a magnetometer), a lidar sensing device, an image sensor, an infrared sensor, or an ultrasonic sensor. encoder, wheel encoder, other type of sensor, or a combination thereof. The sensor 132 has the ability to sense environmental information or the robot's motion state, and the sensing data generated by it can be used for positioning, navigation and map construction of the autonomous mobile robot 130 .

The autonomous mobile robot 130 is wirelessly connected to the local server device 120 . In some embodiments, the wireless communication module 134 may include an antenna and a wireless transceiver to implement wireless data transmission. The autonomous mobile robot 130 can use the wireless communication module 134 to receive data from the local server device 120 and can use the wireless communication module 134 to transmit data to the local server device 120 . The wireless communication module 134 and the wireless communication module 124 can support the same wireless communication standard and communicate with each other through a wireless local area network deployed in the operating environment. For example, the wireless communication module 134 and the wireless communication module 124 can support the 5G communication standard and communicate with each other through a 5G private network deployed in the operating environment.

In some embodiments, the mobile device 135 has mobility capabilities so that the autonomous mobile robot 130 can move on the ground by itself. In some embodiments, the mobile device 135 is an electromechanical device with wheels, and electricity can drive a motor to drive the wheels to rotate, so that the autonomous mobile robot 130 can move on the ground by itself through wheel rotation.

In this article, storage devices (such as storage devices 111, 121, 131) can be used to store instructions, program codes, software modules, etc., and can be any type of fixed or removable random access memory (random access memory). memory (RAM), read-only memory (ROM), flash memory (flash memory), hard disk or other similar device, integrated circuit, or combination thereof.

Here, the processor (such as the processors 113, 123, 133) may be a central processing unit (CPU), an application processor (AP), or other programmable general-purpose or Special purpose microprocessor (microprocessor), digital signal processor (DSP), image signal processor (ISP), graphics processing unit (GPU) or other similar devices, products body circuit or combination thereof.

FIG. 2 is a flow chart of an autonomous mobile robot control method according to an embodiment of the present invention, and the method flow of FIG. 2 can be implemented by the autonomous mobile robot control system 10 of FIG. 1 . In order to make the concept of the present invention easier to understand, FIG. 3A and FIG. 3B will be supplemented for explanation below. FIG. 3A is a schematic diagram of a software function module of a local server device according to an embodiment of the present invention. FIG. 3B is a schematic diagram of a software function module of a local server device according to an embodiment of the present invention. As shown in FIG. 3A and FIG. 3B , the storage device 121 and the storage device 111 may respectively record multiple software modules.

In step S210, at least one autonomous mobile robot 130 wirelessly transmits the sensing data to the local server device 120. Specifically, the sensor 132 can sense environmental information or the robot's motion state, and the autonomous mobile robot 130 can transmit the sensed data to the local server device 120 through the wireless communication module 134 . The above-mentioned sensing data is, for example, inertial sensing data, lidar sensing data, ranging data, or image sensing data, etc.

In step S220, the local server device 120 uses the sensing data to perform positioning operations and navigation operations of at least one autonomous mobile robot 130, and the local server device 120 generates and wirelessly transmits navigation control instructions. In some embodiments, the local server device 120 may utilize simultaneous localization and mapping (SLAM) technology to perform autonomous processing based on sensing data. Positioning operation and navigation operation of the mobile robot 130. That is, the local server device 120 can execute the SLAM algorithm according to the sensing data provided by the autonomous mobile robot 130 to obtain the positioning position of the autonomous mobile robot 130 and generate navigation control instructions. The above-mentioned navigation control instructions are used to control the moving direction, moving speed or moving distance of the autonomous mobile robot 130, etc. The local server device 120 can transmit navigation control instructions to the autonomous mobile robot 130 through the wireless communication module 124 .

As shown in FIG. 3A , the positioning module 1211 of the local server device 120 can use the sensing data to perform the positioning operation of the autonomous mobile robot 130 . The navigation module 1212 of the local server device 120 may utilize the sensing data to perform navigation operations of the autonomous mobile robot 130 . The map module 1213 of the local server device 120 can create an environmental map of the working environment and/or record the environmental map of the working environment based on the sensing data.

In step S230, at least one autonomous mobile robot 130 receives a navigation control instruction from the local server device 120 and moves according to the navigation control instruction. In detail, the autonomous mobile robot 130 can control the mobile device 135 according to the navigation control instruction, so that the autonomous mobile robot 130 can move to the destination along the navigation path. It can be seen that the autonomous mobile robot 130 does not need to be responsible for the huge calculations of positioning operations and navigation operations, but moves according to the navigation control instructions provided by the local server device 120 . Therefore, the hardware cost of the autonomous mobile robot 130 can be reduced, so that the deployment of a large number of autonomous mobile robots 130 can be more in line with actual needs.

In step S240, the local server device 120 provides actual status information of at least one autonomous mobile robot 130 to the cloud server device 110. The actual status information of the autonomous mobile robot 130 may include the machine operation of the autonomous mobile robot 130. row parameters and/or sensing data of the sensor 132 . For example, the actual status information of the autonomous mobile robot 130 may include current level, voltage level, real-time moving speed, real-time angular speed, wheel rotation amount, inertial sensing data or a combination thereof.

Specifically, during the movement of the autonomous mobile robot 130, the autonomous mobile robot 130 can collect actual status information by itself and report the actual status information to the local server device 120 through the wireless communication module 134. Correspondingly, the local server device 120 can transmit the actual status information of the autonomous mobile robot 130 to the cloud server device 110 via the network N1. As shown in FIG. 3A , the management module 1214 of the local server device 120 can receive and manage the actual status information of each autonomous mobile robot 130 , and transmit the actual status information of each autonomous mobile robot 130 to the cloud server device 110 . As shown in FIG. 3B , the actual status information management module 1114 of the cloud server device 110 can receive the actual status information of the autonomous mobile robot 130 from the local server device 120 and manage the actual status information of the autonomous mobile robot 130 .

In step S250 , the cloud server device 110 simulates the virtual state information of the at least one autonomous mobile robot 130 according to the robot mathematical model of the at least one autonomous mobile robot 130 . The robot mathematical model of the autonomous mobile robot 130 is established in advance and stored in the cloud server device 110, which may include a dynamic model or a state space model of the autonomous mobile robot 130, etc. A robot mathematical model can be composed of one or more mathematical functions. Given the model input data, the robot mathematical model can generate virtual state information that simulates the autonomous mobile robot 130 . The virtual status information of the autonomous mobile robot 130 may include virtual current level, virtual voltage level, Virtual moving speed, virtual angular velocity, virtual wheel rotation amount, virtual inertia sensing value or a combination thereof. In other words, after determining the navigation path, the virtual state information of the autonomous mobile robot 130 during movement can be estimated using the robot mathematical model.

As shown in FIG. 3B , the running state simulation module 1112 of the cloud server device 110 can use a pre-established robot mathematical model to simulate and estimate the virtual state information of the autonomous mobile robot 130 . The map management module 1113 of the cloud server 110 can record the environment map of the operating environment, which can be used to generate virtual state information of the autonomous mobile robot 130 .

In step S260, when the actual status information does not match the virtual status information, the cloud server device 110 performs a navigation correction operation. As shown in FIG. 3B , the intelligent decision-making module 1111 of the cloud server device 110 can compare the actual state information and the virtual state information to detect whether the autonomous mobile robot 130 has unexpected erroneous behavior. When detecting that the autonomous mobile robot 130 has unexpected erroneous behavior, the intelligent decision-making module 1111 can perform navigation correction operations. For example, when the autonomous mobile robot 130 is accidentally kicked by a person or slips due to site factors, the autonomous mobile robot 130 may produce undesirable displacement or unsatisfactory operating status. Correspondingly, the cloud server device 110 can initiate a navigation correction operation because the actual state information does not match the virtual state information, so that the autonomous mobile robot 130 will not get lost.

In some embodiments, when the cloud server device 110 performs a navigation correction operation, the cloud server device 110 controls the local server device 120 to re-estimate the position information of the autonomous mobile robot 130 . That is, when an autonomous mobile machine is detected When the robot 130 behaves unexpectedly, the local server device 120 can re-estimate the position information of the autonomous mobile robot 130 based on the sensing data provided by the autonomous mobile robot 130, so that the autonomous mobile robot 130 can return to normal working status as soon as possible. , for example, causing the autonomous mobile robot 130 to return to the previously planned navigation path from the current location. Or, in some embodiments, the cloud server device 110 can use an artificial intelligence model to determine navigation correction operations based on actual status information, so as to perform route changes, task adjustments, or other adjustment operations based on the artificial intelligence model. Based on this, the cloud server device 110 can detect unexpected problems in the autonomous mobile robot 130 in real time, and use navigation correction operations to return the autonomous mobile robot 130 to normal operation as soon as possible to ensure the operational reliability of the autonomous mobile robot 130 .

FIG. 4 is a flow chart of an autonomous mobile robot control method according to an embodiment of the present invention, and the method flow of FIG. 4 can be implemented by the autonomous mobile robot control system 10 of FIG. 1 .

In step S410, the cloud server device 110 schedules one of the at least one autonomous mobile robot 130 to perform the task according to the task content. In detail, the task content may include destination, task type or moving target object, etc. The cloud server device 110 can select a suitable autonomous mobile robot 130 to perform the task according to the task content.

In step S420, the cloud server device 110 determines the navigation information of at least one autonomous mobile robot 130 according to the task content of a task, and provides the navigation information of the at least one autonomous mobile robot 130 to the local server device 120. In subsequent steps, the local server device 120 may perform at least one autonomous migration based on the navigation information. navigation operation of the mobile robot 130. Specifically, navigation information may include starting points, destinations, stopping points, prohibited areas, walkable areas, or best routes, etc. When the local server device 120 performs a navigation operation, the local server device 120 may determine a navigation path based on the navigation information and instruct the scheduled autonomous mobile robot 130 to move along the navigation path.

In step S430, at least one autonomous mobile robot 130 wirelessly transmits the sensing data to the local server device 120. In step S440, the local server device 120 uses the sensing data to perform positioning operations and navigation operations of at least one autonomous mobile robot 130, and the local server device 120 generates and wirelessly transmits navigation control instructions.

In step S450, at least one autonomous mobile robot 130 receives the navigation control instruction from the local server device 120 and moves according to the navigation control instruction. In step S460, the local server device 120 provides actual status information of at least one autonomous mobile robot 130 to the cloud server device 110. In step S470, the cloud server device 110 simulates the virtual state information of the at least one autonomous mobile robot 130 according to the robot mathematical model of the at least one autonomous mobile robot 130. The detailed implementation contents of steps S410 to S470 have been described in the previous embodiments and will not be described again here.

In step S480, the cloud server device 110 determines whether the actual status information matches the virtual status information. For example, the cloud server device 110 may determine whether the difference between the actual status information and the virtual status information is greater than a threshold. If the difference between the actual state information and the virtual state information is greater than the threshold, it can be determined that the actual state information and the virtual state information do not match. On the contrary, if the actual status information and the virtual status If the difference between the state information is not greater than the threshold, it can be determined that the actual state information is consistent with the virtual state information. For example, if the difference between the real-time moving speed of the autonomous mobile robot 130 and the virtual moving speed simulated by the robot's mathematical model is greater than the threshold value, the cloud server device 110 may determine that the actual status information does not match the virtual status information, which means Something unexpected happens.

If the determination in step S480 is negative, in step S490, when the actual status information does not match the virtual status information, the cloud server device 110 performs a navigation correction operation. The detailed implementation content of step S490 has been described in the previous embodiments and will not be described again here.

FIG. 5 is a flow chart of an autonomous mobile robot control method according to an embodiment of the present invention, and the method flow of FIG. 5 can be implemented by the autonomous mobile robot control system 10 of FIG. 1 .

In step S510, at least one autonomous mobile robot 130 wirelessly transmits the sensing data to the local server device 120. In step S520, the local server device 120 uses the sensing data to perform positioning operations and navigation operations of at least one autonomous mobile robot 130, and the local server device 120 generates and wirelessly transmits navigation control instructions. In step S530, at least one autonomous mobile robot 130 receives the navigation control instruction from the local server device 120 and moves according to the navigation control instruction.

In step S540, the local server device 120 provides actual status information of at least one autonomous mobile robot 130 to the cloud server device 110. In step S550, the cloud server device 110 simulates the virtual state data of the at least one autonomous mobile robot 130 according to the robot mathematical model of the at least one autonomous mobile robot 130. News. In step S560, when the actual status information does not match the virtual status information, the cloud server device 110 performs a navigation correction operation. The detailed implementation contents of steps S510 to S560 have been described in the previous embodiments and will not be described again here.

It should be noted that in step S570, at least one autonomous mobile robot 130 reports sensing data and machine operating parameters to the cloud server device 110 through the local server device 120. During the operation of the autonomous mobile robot 130, the autonomous mobile robot 130 collects sensing data and machine operating parameters generated by the sensor 13, and reports the sensing data and machine operating parameters to the cloud server device through the local server device 120. 110. Machine operating parameters may include current level, voltage level, real-time movement speed, or real-time angular velocity, etc.

In step S580, the cloud server device 110 detects the health status of at least one autonomous mobile robot 130 based on the sensing data and machine operating parameters. In some embodiments, the cloud server device 110 can input the sensing data and machine operating parameters of the autonomous mobile robot 130 into the machine learning model to estimate the health status of the autonomous mobile robot 130 . For example, the machine learning model may output an assessed health score of the autonomous mobile robot 130 . The trained machine learning model can be recorded in the cloud server device 110 .

In step S590, the cloud server device 110 stops the operation of the at least one autonomous mobile robot 130 or provides a maintenance notification according to the health status of the at least one autonomous mobile robot 130. When the health status of the autonomous mobile robot 130 meets the maintenance warning conditions, the cloud server device 110 provides a maintenance notification related to the autonomous mobile robot 130 to the administrator. For example, the cloud server device 110 can notify the maintenance Provided to the local server device 120 or the administrator's computer or mobile phone. When the health status of the autonomous mobile robot 130 meets the conditions for stopping operation, the cloud server device 110 can control the autonomous mobile robot 130 to stop running through the local server device 120 .

For example, when the assessed health score of the autonomous mobile robot 130 is less than the first threshold, the cloud server device 110 may provide a maintenance notification. When the evaluated health score of the autonomous mobile robot 130 is less than the second threshold, the cloud server device 110 may stop the autonomous mobile robot 130 from continuing to run. The first threshold value is different from the second threshold value.

FIG. 6 is a flow chart of an autonomous mobile robot control method according to an embodiment of the present invention, and the method flow of FIG. 6 can be implemented by the autonomous mobile robot control system 10 of FIG. 1 .

In step S602, one of the at least one autonomous mobile robot 130 moves in the working environment, and the local server device 120 establishes an environment map of the working environment based on the sensing data provided by one of the at least one autonomous mobile robot 130. Specifically, the local server device 120 can control an autonomous mobile robot 130 to move along a scanning path in the operating environment, so as to establish and draw the operating environment based on the sensing data and SLAM technology provided by controlling the autonomous mobile robot 130 environmental map.

In step S604, the local server device 120 uploads the environment map of the operating environment to the cloud server device 110. The cloud server device 110 will record the environment map of the operating environment.

In step S606, the cloud server device 110 sets the environment map multiple sites, and provide site information of the multiple sites to the local server device 120. Specifically, the administrator can set multiple sites in the environment map through the cloud server device 110 . These stations may include charging stations or work stations, among others. After the administrator completes the site settings, the cloud server device 110 can provide site information of multiple sites to the local server device 120 . It can be seen that even if the administrator is not located at the working environment site, the site in the working environment can still be deployed remotely through the cloud server device 110 . Moreover, these site information can be shared by all autonomous mobile robots 130 managed by the local server device 120, so the administrator does not need to repeatedly perform the site setting process for each autonomous mobile robot 130.

In step S608, the local server device 120 adjusts the environment map to generate another environment map suitable for the other one of the at least one autonomous mobile robot 130. Specifically, the environment map generated based on a certain autonomous mobile robot 130 actually performing spatial sensing in the working environment can be used for other autonomous mobile robots 130 through the local server device 120 . In this way, managers do not need to control a large number of autonomous mobile robots 130 one by one to actually walk in the working environment to establish an environmental map for each autonomous mobile robot 130, which greatly simplifies the process of establishing an environmental map.

In addition, since each autonomous mobile robot 130 has manufacturing tolerances, the local server device 120 can adjust the environment map established by a certain autonomous mobile robot 130 to generate another environment map of another autonomous mobile robot 130 . The local server device 120 can perform map adjustment based on the error information of another autonomous mobile robot 130, and the error information (such as the height or angle of the sensor 132, etc.) can be learned through a prior robot calibration procedure. In this way, in While greatly simplifying the mapping process, the local server device 120 can still generate an environment map suitable for each autonomous mobile robot 130 .

In step S610, at least one autonomous mobile robot 130 wirelessly transmits the sensing data to the local server device 120. In step S612, the local server device 120 uses the sensing data to perform positioning operations and navigation operations of at least one autonomous mobile robot 130, and the local server device 120 generates and wirelessly transmits navigation control instructions. In some embodiments, the local server device 120 can perform positioning operations and navigation operations of at least one of the autonomous mobile robots 130 according to the environment map. In addition, the local server device 120 can perform positioning operations and navigation operations of at least one other of the autonomous mobile robots according to another environment map.

In step S614, at least one autonomous mobile robot 130 receives the navigation control instruction from the local server device 120 and moves according to the navigation control instruction. In step S616, the local server device 120 provides actual status information of at least one autonomous mobile robot 130 to the cloud server device 110. In step S618, the cloud server device 110 simulates the virtual state information of the at least one autonomous mobile robot 130 according to the robot mathematical model of the at least one autonomous mobile robot 130. In step S620, when the actual status information does not match the virtual status information, the cloud server device 110 performs a navigation correction operation. The detailed implementation contents of steps S610 to S520 have been described in the previous embodiments and will not be described again here.

In summary, in embodiments of the present invention, since the positioning operation and navigation operation of the autonomous mobile robot are performed by the local server device, the hardware cost requirements for the autonomous mobile robot can be reduced, and a large number of parts of the autonomous mobile robot can be The department can be more in line with actual needs. In addition, by comparing the virtual state information simulated by the robot's mathematical model with the actual state information of the autonomous mobile robot in the real physical environment, the cloud server device can instantly detect whether unexpected problems occur in the autonomous mobile robot and execute accordingly. Navigation repair operation so that the autonomous mobile robot can return to normal operation as soon as possible. Based on this, the reliability and stability of autonomous mobile robots can be greatly improved. In addition, the cloud server device can detect the health status of the autonomous mobile robot in real time and provide appropriate countermeasures, thereby extending the service life of the autonomous mobile robot and avoiding accidents. Moreover, embodiments of the present invention can realize the function of remotely synchronously deploying multiple autonomous mobile robots, thereby greatly improving the convenience and efficiency of deploying multiple autonomous mobile robots.

Although the present invention has been disclosed above through embodiments, they are not intended to limit the present invention. Anyone with ordinary knowledge in the technical field may make some modifications and modifications without departing from the spirit and scope of the present invention. Therefore, The protection scope of the present invention shall be determined by the appended patent application scope.

S210~S260: steps

Claims (16)

An autonomous mobile robot control system, including: a cloud server device; a local server device connected to the cloud server device; and at least one autonomous mobile robot wirelessly connected to the local server device and sending sensing data wirelessly transmitting to the local server device, wherein the local server device uses the sensing data to perform a positioning operation and a navigation operation of the at least one autonomous mobile robot, and generates and wirelessly transmits a navigation control instruction, The at least one autonomous mobile robot receives the navigation control instruction from the local server device and moves according to the navigation control instruction, wherein the local server device provides actual status information of the at least one autonomous mobile robot. To the cloud server device, the cloud server device simulates the virtual state information of the at least one autonomous mobile robot according to the robot mathematical model of the at least one autonomous mobile robot. When the actual state information and the virtual state When the information does not match, the cloud server device performs a navigation correction operation, wherein one of the at least one autonomous mobile robot moves in an operating environment, and the local server device performs a navigation correction operation according to the at least one autonomous mobile robot. The sensing data provided by the one establishes an environmental map of the operating environment, and the local server device adjusts the environmental map to generate a map suitable for the operating environment. Another environment map of at least one of the other autonomous mobile robots, the local server device performs the positioning operation and the positioning operation of the other of the at least one autonomous mobile robot according to the other environment map Navigation operations. The autonomous mobile robot control system according to claim 1, wherein the cloud server device determines the navigation information of the at least one autonomous mobile robot according to the task content of a task, and transfers the navigation information of the at least one autonomous mobile robot to Navigation information is provided to the local server device, causing the local server device to perform the navigation operation of the at least one autonomous mobile robot according to the navigation information. The autonomous mobile robot control system of claim 2, wherein the local server device determines a navigation path based on the navigation information, and the cloud server device schedules the at least one autonomous mobile robot based on the task content One of them performs said task. The autonomous mobile robot control system of claim 1, wherein when the cloud server device performs the navigation correction operation, the cloud server device controls the local server device to re-estimate the at least one autonomous movement The robot’s location information. As in the autonomous mobile robot control system of claim 1, the at least one autonomous mobile robot reports the sensing data and a machine operating parameter to the cloud server device via the local server device, wherein the cloud server The server device detects the health status of the at least one autonomous mobile robot based on the sensing data and the machine operating parameters. The autonomous mobile robot control system according to claim 5, wherein the cloud server device stops the operation of the at least one autonomous mobile robot or provides a maintenance notification according to the health status of the at least one autonomous mobile robot. The autonomous mobile robot control system according to claim 1, wherein the local server device performs the positioning operation and the navigation operation of the one of the at least one autonomous mobile robot according to the environment map. The autonomous mobile robot control system of claim 7, wherein the local server device uploads the environment map of the operating environment to the cloud server device, and the cloud server device is located on the environment map Multiple sites are set in the server, and site information of the multiple sites is provided to the local server device. An autonomous mobile robot control method, suitable for an autonomous mobile robot control system, wherein the autonomous mobile robot control system includes a cloud server device, a local server device, and at least one autonomous mobile robot, the method includes: At least one autonomous mobile robot wirelessly transmits sensing data to the local server device; the local server device uses the sensing data to perform a positioning operation and a navigation operation of the at least one autonomous mobile robot, and A navigation control command is generated and wirelessly transmitted by the local server device; the at least one autonomous mobile robot receives the navigation control command from the local server device and moves according to the navigation control command; by the at least one autonomous mobile robot The local server device stores the actual data of the at least one autonomous mobile robot The status information is provided to the cloud server device; the cloud server device simulates the virtual status information of the at least one autonomous mobile robot according to the robot mathematical model of the at least one autonomous mobile robot; and when the actual status information When it is inconsistent with the virtual state information, the cloud server device performs a navigation correction operation. The method further includes: moving one of the at least one autonomous mobile robot in an operating environment, and using the The local server device establishes an environmental map of the operating environment based on the sensing data provided by the one of the at least one autonomous mobile robot; and the local server device adjusts the environmental map to generate Another environment map suitable for the other one of the at least one autonomous mobile robot, wherein the local server device executes the other one of the at least one autonomous mobile robot according to the another environment map. Positioning operations and the navigation operations. The method for controlling an autonomous mobile robot as described in claim 9, further comprising: determining, by the cloud server device, the navigation information of the at least one autonomous mobile robot according to the task content of a task, and sending the at least one The navigation information of the autonomous mobile robot is provided to the local server device, wherein the local server device uses the sensing data to perform the positioning operation and the navigation operation of the at least one autonomous mobile robot. Steps include: The local server device performs the navigation operation of the at least one autonomous mobile robot according to the navigation information. The autonomous mobile robot control method according to claim 10, wherein the method further includes: scheduling one of the at least one autonomous mobile robot to perform the task according to the task content by the cloud server device; and The local server device determines a navigation path based on the navigation information. The autonomous mobile robot control method according to claim 9, wherein when the actual state information does not match the virtual state information, the step of performing the navigation correction operation by the cloud server device includes: when the If the actual state information does not match the virtual state information, the cloud server device controls the local server device to re-estimate the position information of the at least one autonomous mobile robot. The method for controlling an autonomous mobile robot according to claim 9, further comprising: reporting the sensing data and a machine operating parameter to the cloud server by the at least one autonomous mobile robot via the local server device. and the cloud server device detects the health status of the at least one autonomous mobile robot based on the sensing data and the machine operating parameters. The method for controlling an autonomous mobile robot according to claim 13, further comprising: using the cloud server device to control the autonomous mobile robot according to the health of the at least one autonomous mobile robot. The health state stops the operation of the at least one autonomous mobile robot or provides a maintenance notification. The autonomous mobile robot control method according to claim 9, wherein the local server device performs the positioning operation and the navigation operation of the one of the at least one autonomous mobile robot according to the environment map. The autonomous mobile robot control method according to claim 15, the method further includes: uploading the environment map of the operating environment to the cloud server device by the local server device; and uploading the environment map of the operating environment to the cloud server device by the cloud server The server device sets multiple sites in the environment map and provides site information of the multiple sites to the local server device.