Multi-scene composite collaborative robot control method and related device

Abstract

The invention discloses a multi-scene composite collaborative robot control method and a related device, and the method comprises the steps that a far-end control center obtains a collaborative task, generates a collaborative instruction based on the collaborative task, and issues the collaborative instruction to a corresponding target collaborative robot, and the collaborative instruction comprises a target position where the collaborative task is located; when the target collaborative robot receives the collaboration instruction, current operation areas of other collaborative robots shared by the far-end control center are obtained in real time; path planning processing is executed based on the current position of the target collaborative robot, the current operation areas of the other collaborative robots and the target position, and operation planning path information of the target collaborative robot is obtained; and the target collaborative robot executes a collaborative task in the collaborative instruction based on the operation planning path information. In the embodiment of the invention, the cooperative task is executed through the operation planning path information, so that the blockage phenomenon of the multiple cooperative robots can be avoided, and the working efficiency of the multiple cooperative robots is improved.

Description

Technical Field

[0001] The present invention relates to the field of robot control technology, and in particular to a multi-scenario composite collaborative robot control method and related devices. Background Art

[0002] In recent years, with the rapid development of information technology and computer technology, automated production lines have been increasingly widely used, and factories such as "fully automated factories", "digital factories" and "lighthouse factories" have emerged. With the birth of new factories, the production lines will also undergo earth-shaking changes accordingly. Compared with the previous all-manual production lines, the new factories almost use fully automated equipment, from production lines, transportation equipment, to monitoring equipment, all completed independently. In addition, there are some production lines with high requirements, such as dust-free production factories, chip production factories, etc., which require full automation in the factory; therefore, in order to meet the development needs of automated factories, a multi-scenario composite collaborative robot control method is proposed to meet most of the application needs of automated factories.

[0003] The prior art discloses a discrete production line unmanned automatic transport robot system and method (patent number: CN202410773153.3) discloses a discrete production line unmanned automatic transport robot system, including a production line, a roller robot, a robot management system, and a factory management system, but it mainly uses the roller structure for expansion, has no gripper mechanism, and is mainly concentrated in the roller application field; or discloses a smart factory intelligent robot control management method and system (patent number: CN202211550919.9) discloses a smart factory intelligent robot control management method and system. The present invention obtains the basic information and handling information of each driving route of the target handling robot, and finally comprehensively obtains the recommended coefficients of each reference route of the target handling robot, and screens out the best route for the target handling robot. However, the invention mainly focuses on a single intelligent robot, which will have a great impact once it encounters a road surface with hidden dangers. Summary of the invention

[0004] The purpose of the present invention is to overcome the shortcomings of the prior art. The present invention provides a multi-scenario composite collaborative robot control method and related devices. By executing collaborative tasks through job planning path information, congestion of multiple collaborative robots can be avoided, thereby improving the work efficiency of multiple collaborative robots.

[0005] In order to solve the above technical problems, an embodiment of the present invention provides a multi-scenario composite collaborative robot control method, which is applied to a plurality of collaborative robots, wherein the plurality of collaborative robots are communicatively connected to a remote control center, and the collaborative robots are composed of a robot walking system, a robot cargo placement area, and a robot grasping system; the method includes:

[0006] The remote control center obtains a collaborative task, generates a collaborative instruction based on the collaborative task, and sends the collaborative instruction to the corresponding target collaborative robot, wherein the collaborative instruction includes a target position of the collaborative task;

[0007] When the target collaborative robot receives the collaborative instruction, it obtains the current operation area of ​​other collaborative robots shared by the remote control center in real time;

[0008] Execute path planning processing based on the current position of the target collaborative robot, the current working area of ​​other collaborative robots and the target position to obtain the working planning path information of the target collaborative robot;

[0009] The target collaborative robot executes the collaborative task in the collaborative instruction based on the operation planning path information.

[0010] Optionally, the collaborative task is to arrive at a designated first target location to load the target cargo, and then arrive at a designated second target location to unload the loaded target cargo.

[0011] Optionally, the remote control center obtains the collaboration task, and generates a collaboration instruction based on the collaboration task, including:

[0012] The remote control center obtains the collaborative task by receiving an input operation of a management user;

[0013] Calculate the number of collaborative robots required based on the number of target goods in the collaborative task to obtain the number of collaborative robots required to be allocated for the collaborative task;

[0014] A collaboration instruction corresponding to the collaboration task is generated based on the number of collaborative robots required to be assigned to the collaboration task.

[0015] Optionally, generating a collaboration instruction corresponding to the collaboration task based on the number of collaborative robots required to be allocated to the collaboration task includes:

[0016] The remote control center sorts the idle collaborative robots among the plurality of collaborative robots according to the length of idle time and the length of time until the collaborative robots in operation complete the current collaborative task, and generates a sorted list of collaborative task arrangements for the plurality of collaborative robots;

[0017] Based on the number of collaborative robots required to be assigned to the collaborative task, a corresponding number of collaborative robots are selected from the collaborative task arrangement sorting list as a plurality of collaborative robots to be executed for the collaborative task;

[0018] The remote control center obtains multiple MAC addresses corresponding to multiple collaborative robots to perform collaborative tasks, and generates collaborative instructions corresponding to the collaborative tasks based on the multiple MAC addresses.

[0019] Optionally, when receiving the collaboration instruction, the target collaborative robot obtains the current operation area of ​​other collaborative robots shared by the remote control center in real time, including:

[0020] When the target collaborative robot receives the collaborative instruction, generating a two-way communication instruction based on the collaborative instruction;

[0021] The target collaborative robot establishes a two-way real-time communication channel with the remote control center during task execution based on the two-way communication instruction, and obtains the current working area of ​​other collaborative robots shared by the remote control center in real time based on the two-way real-time communication channel.

[0022] Optionally, performing path planning processing based on the current position of the target collaborative robot, the operation areas of other collaborative robots, and the target position to obtain the operation planning path information of the target collaborative robot includes:

[0023] The target collaborative robot divides the current operation area of ​​other collaborative robots into a non-drivable area;

[0024] The target collaborative robot performs path planning processing based on the current position and the target position in a manner of the shortest driving path after avoiding the non-drivable area, and obtains the operation planning path information of the target collaborative robot.

[0025] Optionally, the target collaborative robot executes the collaborative task in the collaborative instruction based on the operation planning path information, including:

[0026] After controlling the target collaborative robot to reach a specified first target position based on the operation planning path information, controlling the robot grasping system to grasp the target cargo and place it in the robot cargo placement area;

[0027] After completing the grabbing of the target cargo, the target collaborative robot is controlled to reach the second target position based on the operation planning path information, and the robot grabbing system is controlled to grab the target cargo in the robot cargo placement area to complete the unloading operation.

[0028] In addition, an embodiment of the present invention further provides a multi-scenario composite collaborative robot control device, which is applied to a plurality of collaborative robots, wherein the plurality of collaborative robots are communicatively connected to a remote control center, and the collaborative robots are composed of a robot walking system, a robot cargo placement area, and a robot grasping system; the device includes:

[0029] Sending module: used for the remote control center to obtain the collaborative task, generate a collaborative instruction based on the collaborative task, and send the collaborative instruction to the corresponding target collaborative robot, wherein the collaborative instruction includes the target position of the collaborative task;

[0030] Real-time acquisition module: used for the target collaborative robot to obtain the current operation area of ​​other collaborative robots shared by the remote control center in real time when receiving the collaborative instruction;

[0031] Path planning module: used to perform path planning processing based on the current position of the target collaborative robot, the current working area of ​​other collaborative robots and the target position, and obtain the working planning path information of the target collaborative robot;

[0032] Task execution module: used for the target collaborative robot to execute the collaborative task in the collaborative instruction based on the operation planning path information.

[0033] In addition, an embodiment of the present invention also provides a multi-scenario composite collaborative robot control method system, the system includes several collaborative robots and a remote control center arranged in an operating area, multiple local area network devices are arranged in the operating area, and the several collaborative robots are communicated with the remote control center through the local area network devices; the system is configured to implement the multi-scenario composite collaborative robot control method as described in any one of the above.

[0034] In addition, an embodiment of the present invention further provides a computer-readable storage medium for storing a computer program or code. When the computer program or code is executed by a processor, a multi-scenario composite collaborative robot control method as described in any one of the above is implemented.

[0035] During the specific implementation of the present invention, executing collaborative tasks through job planning path information can avoid the congestion of multiple collaborative robots, thereby improving the work efficiency of multiple collaborative robots; that is, through real-time LAN communication between multiple collaborative robots and the remote control center, real-time data transmission is realized, and when planning and controlling, the global path information is combined to autonomously plan the robot's safe driving path to avoid congestion of multiple robots; through the all-round identification and grasping of the target goods by the robot grasping system of multiple collaborative robots, the object recognition accuracy is greatly enhanced, and the work efficiency of the collaborative robots is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0037] Figure 1 is a flow chart of a multi-scenario composite collaborative robot control method in an embodiment of the present invention;

[0038] Figure 2 is a flow chart of a multi-scenario composite collaborative robot control method in another embodiment of the present invention;

[0039] Figure 3 2 is a schematic diagram of the structure of a multi-scenario composite collaborative robot control device according to an embodiment of the present invention;

[0040] Figure 4 Schematic diagram of the structure of a multi-scenario composite collaborative robot control system in an embodiment of the present invention;

[0041] Figure 5 Schematic diagram of the structure of the collaborative robot in an embodiment of the present invention;

[0042] Figure 6 is a top view of the collaborative robot in an embodiment of the present invention. DETAILED DESCRIPTION

[0043] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0044] For example, see Figure 1 , Figure 1 It is a flow chart of the multi-scenario composite collaborative robot control method in an embodiment of the present invention.

[0045] like Figure 1 As shown, a multi-scenario composite collaborative robot control method is applied to a plurality of collaborative robots, wherein the plurality of collaborative robots are communicatively connected to a remote control center, and the collaborative robots are composed of three parts: a robot walking system, a robot cargo placement area, and a robot grasping system;

[0046] In the specific implementation of the present invention, for collaborative robots, please refer to Figure 5 and Figure 6 ; That is, the collaborative robot consists of three parts: robot walking system, robot cargo placement area, and robot grasping system; among them, the robot walking system mainly includes intelligent chassis system, intelligent chassis controller, laser radar, ultrasonic radar, dual-gun charging port, remote control module, display, loudspeaker, wheels, etc.; the intelligent chassis system mainly includes drive control system, electric steering system, electric control braking system, etc., which mainly realize the robot's driving, steering and braking functions, and are the basis for safe and stable walking; the intelligent chassis controller mainly realizes the precise control of the drive control system, electric steering system, and electric control braking system, and adopts a domain control system; the laser radar adopts a dual laser radar solution, that is, a laser radar is arranged before and after the robot walks, which mainly senses the robot's surrounding environment to ensure the robot The robot can avoid obstacles encountered during driving and reach its destination smoothly; 8 ultrasonic radars are used, that is, two ultrasonic radars are arranged at four positions on the robot chassis, which are mainly used to monitor close-range obstacles around the robot, and cooperate with the laser radar to accurately identify long- and short-range obstacles during the robot's walking process to ensure the safety of the robot's walking; the dual-gun charging port adopts two charging port modes, which can quickly charge the robot and enter the working state. It is especially suitable for all-weather automated production factories, fast charging and fast rotation; the remote control module is mainly to realize the real-time connection between a single robot and the remote control center for real-time data exchange, that is, the robot uploads its own position and implementation status information to the remote control center, and receives the position information of other robots sent by the remote control center.

[0047] The robot grasping system is mainly composed of motors (a total of 6 motors), cameras, and clamping devices; the motors are mainly responsible for adjusting the position, that is, they are continuously adjusted through 5 motors (motors 1-5). Motor 1 controls the overall left and right rotation of the grasping device, that is, it rotates left and right around the Z-axis; Motor 2 controls the Y-axis rotation of the grasping device, Motor 3 controls the lifting range of the robot grasping system, Motor 4 controls the close-range position of the grasping mechanism, and Motor 5 controls to move the clamping device to the placement area or external working area to facilitate the grasping mechanism to grasp the goods smoothly; Motor 6 mainly controls the width of the grasping mechanism, so that it can be suitable for grasping goods of different widths and sizes, further improving the application scenarios of the robot and expanding the application needs of the robot; the dual cameras are mainly for object recognition. The dual cameras are located on both sides of the clamping device. They have two main functions. First, they can help the grasping mechanism to locate the goods. Second, by monitoring the surrounding environment of the robot grasping mechanism, ensure the safety of the robot grasping process.

[0048] The loudspeaker is mainly used for voice reminders when needed, such as during turning, reversing, and vehicle breakdown; the display is mainly used to display the robot's working status, such as information such as working, remaining battery power, remaining cargo, vehicle fault status (if a fault occurs), etc.

[0049] The method comprises:

[0050] S101: The remote control center obtains a collaborative task, generates a collaborative instruction based on the collaborative task, and sends the collaborative instruction to a corresponding target collaborative robot, wherein the collaborative instruction includes a target position of the collaborative task;

[0051] In the specific implementation process of the present invention, the collaborative task is to arrive at a designated first target location to load the target goods, and then arrive at a designated second target location to unload the loaded target goods.

[0052] Furthermore, the remote control center obtains a collaborative task and generates a collaborative instruction based on the collaborative task, including: the remote control center obtains the collaborative task by receiving input operations from a management user; calculates and processes the required number of collaborative robots based on the number of target goods in the collaborative task to obtain the number of collaborative robots required to be assigned to the collaborative task; and generates a collaborative instruction corresponding to the collaborative task based on the number of collaborative robots required to be assigned to the collaborative task.

[0053] Furthermore, the remote control center sorts the idle collaborative robots among the several collaborative robots according to the length of idle time and the length of time it takes for the collaborative robots in operation to complete the current collaborative tasks, and generates a collaborative task arrangement sorting list for the several collaborative robots; based on the number of collaborative robots required to be assigned to the collaborative task, a corresponding number of collaborative robots are selected from the collaborative task arrangement sorting list as multiple collaborative robots to perform collaborative tasks; the remote control center obtains multiple MAC addresses corresponding to the multiple collaborative robots to perform collaborative tasks, and generates collaborative instructions corresponding to the collaborative tasks based on the multiple MAC addresses.

[0054] Specifically, the remote control center obtains the collaborative task by receiving the input operation of the management user; the collaborative task is to arrive at the designated first target location to load the target goods, and then arrive at the designated second target location to unload the loaded target goods.

[0055] After obtaining the collaborative task, the required number of collaborative robots will be calculated based on the number of target goods in the collaborative task to obtain the number of collaborative robots required to be assigned to the collaborative task; then the collaborative instructions corresponding to the collaborative task will be generated based on the number of collaborative robots required to be assigned to the collaborative task.

[0056] The specific collaborative instructions are generated as follows: the remote control center sorts the idle collaborative robots among several collaborative robots according to the length of idle time and the time length for the collaborative robots in operation to complete the current collaborative tasks, and generates a collaborative task arrangement sorting list for several collaborative robots; then, according to the number of collaborative robots required to be assigned to the collaborative tasks, a corresponding number of collaborative robots are selected from the collaborative task arrangement sorting list as multiple collaborative robots to perform collaborative tasks; and the remote control center obtains multiple MAC addresses corresponding to the multiple collaborative robots to perform collaborative tasks, and finally generates collaborative instructions corresponding to the collaborative tasks through the multiple MAC addresses, and sends the collaborative instructions to the corresponding target collaborative robots.

[0057] S102: When receiving the collaboration instruction, the target collaborative robot obtains the current operation area of ​​other collaborative robots shared by the remote control center in real time;

[0058] During the specific implementation of the present invention, when the target collaborative robot receives the collaborative instruction, it obtains the current working area of ​​other collaborative robots shared by the remote control center in real time, including: when the target collaborative robot receives the collaborative instruction, it generates a two-way communication instruction based on the collaborative instruction; the target collaborative robot establishes a two-way real-time communication channel with the remote control center during task execution based on the two-way communication instruction, and obtains the current working area of ​​other collaborative robots shared by the remote control center in real time based on the two-way real-time communication channel.

[0059] Specifically, when the target collaborative robot receives the collaborative instruction, it generates a two-way communication instruction based on the collaborative instruction; after obtaining the two-way communication instruction, the target collaborative robot will establish a two-way real-time communication channel with the remote control center during task execution through the two-way communication instruction, and at the same time obtain the current working area of ​​other collaborative robots shared by the remote control center in real time through the two-way communication channel.

[0060] S103: performing path planning processing based on the current position of the target collaborative robot, the current working areas of other collaborative robots, and the target position to obtain the working planning path information of the target collaborative robot;

[0061] In the specific implementation process of the present invention, the path planning processing is performed based on the current position of the target collaborative robot, the working area of ​​other collaborative robots and the target position to obtain the working planning path information of the target collaborative robot, including: the target collaborative robot divides the current working area of ​​other collaborative robots into a non-drivable area; the target collaborative robot performs path planning processing based on the current position and the target position in a manner of avoiding the shortest driving path after the non-drivable area to obtain the working planning path information of the target collaborative robot.

[0062] Specifically, the target collaborative robot divides the current operating area of ​​other collaborative robots into a non-drivable area; then the target assisting robot will perform path planning processing according to the current position and the target position in a manner that avoids the shortest driving path after the non-drivable area, and obtain the operating planning path information of the target collaborative robot.

[0063] That is, the target collaborative robots are all connected to the remote control center through a wireless network, while each target collaborative robot is not directly connected to each other, because in a certain area of ​​the factory (target operation area), the use of a local area network can achieve the purpose of real-time information transmission, that is, by building a certain number of local area network devices (routers, etc.) in the factory, each robot can be connected to the remote control center; during the working process of the collaborative robot, people only need to send instructions to the collaborative robot at the remote control center. Generally, the robot starts from the initial position. Whenever the collaborative robot completes the previous task, if it does not receive a new task, it returns to the initial position and waits for new task instructions; but the collaborative robot supports receiving command strings, that is, accepting multiple commands at the same time. For example, a series of commands such as loading at a designated location and unloading at a designated location can be sent from the remote control center to the collaborative robot at the same time. The collaborative robot will recognize that it should go to the designated location to load first, and then It drives autonomously to the next designated location to unload. If a new instruction is received before unloading is completed, the collaborative robot will carry out the new instruction task after unloading is completed without returning to the original position. When receiving a new instruction, the collaborative robot will outline the working area (between the starting point and the end point) where the enterprise collaborative robot is located and the positions of other robots based on its own position and the position information of other collaborative robots received from the remote control center and the working area. For example, after a collaborative robot receives an instruction from the remote control center from the initial position, it obtains the target position point, and then calculates the robot's safe driving path based on the working area (non-drivable area, the positions of other robots), and outlines a regional path sequence (coordinate points, including horizontal and vertical coordinate points) to the target position from the initial position. This method uses the local area network for real-time information sharing, effectively avoids multi-robot congestion, and improves factory production efficiency.

[0064] S104: The target collaborative robot executes the collaborative task in the collaborative instruction based on the operation planning path information.

[0065] During the specific implementation of the present invention, the target collaborative robot executes the collaborative task in the collaborative instruction based on the operation planning path information, including: after controlling the target collaborative robot to reach the specified first target position based on the operation planning path information, controlling the robot grasping system to grasp the target cargo and place it in the robot cargo placement area; after completing the grasping of the target cargo, controlling the target collaborative robot to reach the second target position based on the operation planning path information, and controlling the robot grasping system to grasp the target cargo in the robot cargo placement area to complete the unloading operation.

[0066] Specifically, after controlling the target collaborative robot to reach the specified first target position through the operation planning path information, the robot grasping system is controlled to grasp the target goods and place them in the robot cargo placement area. After completing the grasping of the target goods, the target collaborative robot is controlled to reach the second target position through the operation planning path information, and the robot grasping system is controlled to grasp the target goods in the robot cargo placement area to complete the unloading operation; thereby completing the collaborative task in the collaborative instruction.

[0067] During the specific implementation of the present invention, executing collaborative tasks through job planning path information can avoid the congestion of multiple collaborative robots, thereby improving the work efficiency of multiple collaborative robots; that is, through real-time LAN communication between multiple collaborative robots and the remote control center, real-time data transmission is realized, and when planning and controlling, the global path information is combined to autonomously plan the robot's safe driving path to avoid congestion of multiple robots; through the all-round identification and grasping of the target goods by the robot grasping system of multiple collaborative robots, the object recognition accuracy is greatly enhanced, and the work efficiency of the collaborative robots is improved.

[0068] For example 2, please refer to Figure 2 , Figure 2 It is a flow chart of a multi-scenario composite collaborative robot control method in another embodiment of the present invention.

[0069] like Figure 2 As shown, a multi-scenario composite collaborative robot control method is applied to a plurality of collaborative robots, wherein the plurality of collaborative robots are communicatively connected to a remote control center, and the collaborative robots are composed of a robot walking system, a robot cargo placement area, and a robot grasping system; the method includes:

[0070] S201: The remote control center receives the input operation of the management user to obtain the collaborative task;

[0071] S202: Calculating the number of collaborative robots required based on the number of target goods in the collaborative task to obtain the number of collaborative robots required to be allocated for the collaborative task;

[0072] S203: The remote control center sorts the idle collaborative robots among the plurality of collaborative robots according to the length of idle time and the length of time until the collaborative robots in operation complete the current collaborative task, and generates a sorted list of collaborative task arrangements for the plurality of collaborative robots;

[0073] S204: selecting a corresponding number of collaborative robots from the collaborative task arrangement sorting list based on the number of collaborative robots required to be assigned to the collaborative task as a plurality of collaborative robots to be executed for the collaborative task;

[0074] S205: The remote control center obtains multiple MAC addresses corresponding to multiple collaborative robots to perform collaborative tasks, and generates collaborative instructions corresponding to the collaborative tasks based on the multiple MAC addresses, and sends the collaborative instructions to the corresponding target collaborative robots, wherein the collaborative instructions include the target location of the collaborative tasks;

[0075] S206: When receiving the collaboration instruction, the target collaborative robot obtains the current operation area of ​​other collaborative robots shared by the remote control center in real time;

[0076] S207: performing path planning processing based on the current position of the target collaborative robot, the current working areas of other collaborative robots, and the target position to obtain the working planning path information of the target collaborative robot;

[0077] S208: After controlling the target collaborative robot to reach a designated first target position based on the operation planning path information, controlling the robot grasping system to grasp the target cargo and place it in the robot cargo placement area;

[0078] S209: After completing the grabbing of the target cargo, the target collaborative robot is controlled to reach the second target position based on the operation planning path information, and the robot grabbing system is controlled to grab the target cargo in the robot cargo placement area to complete the unloading operation.

[0079] The specific implementation of the second embodiment can be found in the above embodiments, which will not be described in detail here.

[0080] For example 3, please refer to Figure 3 , Figure 3 It is a schematic diagram of the structural composition of a multi-scenario composite collaborative robot control device in an embodiment of the present invention.

[0081] like Figure 3As shown, a multi-scenario composite collaborative robot control device is applied to a plurality of collaborative robots, wherein the plurality of collaborative robots are communicatively connected to a remote control center, and the collaborative robots are composed of a robot walking system, a robot cargo placement area, and a robot grasping system.

[0082] In the specific implementation of the present invention, for collaborative robots, please refer to Figure 5 and Figure 6 ; That is, the collaborative robot consists of three parts: robot walking system, robot cargo placement area, and robot grasping system; among them, the robot walking system mainly includes intelligent chassis system, intelligent chassis controller, laser radar, ultrasonic radar, dual-gun charging port, remote control module, display, loudspeaker, wheels, etc.; the intelligent chassis system mainly includes drive control system, electric steering system, electric control braking system, etc., which mainly realize the robot's driving, steering and braking functions, and are the basis for safe and stable walking; the intelligent chassis controller mainly realizes the precise control of the drive control system, electric steering system, and electric control braking system, and adopts a domain control system; the laser radar adopts a dual laser radar solution, that is, a laser radar is arranged before and after the robot walks, which mainly senses the robot's surrounding environment to ensure the robot The robot can avoid obstacles encountered during driving and reach its destination smoothly; 8 ultrasonic radars are used, that is, two ultrasonic radars are arranged at four positions on the robot chassis, which are mainly used to monitor close-range obstacles around the robot, and cooperate with the laser radar to accurately identify long- and short-range obstacles during the robot's walking process to ensure the safety of the robot's walking; the dual-gun charging port adopts two charging port modes, which can quickly charge the robot and enter the working state. It is especially suitable for all-weather automated production factories, fast charging and fast rotation; the remote control module is mainly to realize the real-time connection between a single robot and the remote control center for real-time data exchange, that is, the robot uploads its own position and implementation status information to the remote control center, and receives the position information of other robots sent by the remote control center.

[0083] The robot grasping system is mainly composed of motors (a total of 6 motors), cameras, and clamping devices; the motors are mainly responsible for adjusting the position, that is, they are continuously adjusted through 5 motors (motors 1-5). Motor 1 controls the overall left and right rotation of the grasping device, that is, it rotates left and right around the Z-axis; Motor 2 controls the Y-axis rotation of the grasping device, Motor 3 controls the lifting range of the robot grasping system, Motor 4 controls the close-range position of the grasping mechanism, and Motor 5 controls to move the clamping device to the placement area or external working area to facilitate the grasping mechanism to grasp the goods smoothly; Motor 6 mainly controls the width of the grasping mechanism, so that it can be suitable for grasping goods of different widths and sizes, further improving the application scenarios of the robot and expanding the application needs of the robot; the dual cameras are mainly for object recognition. The dual cameras are located on both sides of the clamping device. They have two main functions. First, they can help the grasping mechanism to locate the goods. Second, by monitoring the surrounding environment of the robot grasping mechanism, ensure the safety of the robot grasping process.

[0084] The loudspeaker is mainly used for voice reminders when needed, such as during turning, reversing, and vehicle breakdown; the display is mainly used to display the robot's working status, such as information such as working, remaining battery power, remaining cargo, vehicle fault status (if a fault occurs), etc.

[0085] The device comprises:

[0086] Sending module 301: used for the remote control center to obtain a collaborative task, generate a collaborative instruction based on the collaborative task, and send the collaborative instruction to the corresponding target collaborative robot, wherein the collaborative instruction includes a target position of the collaborative task;

[0087] In the specific implementation process of the present invention, the collaborative task is to arrive at a designated first target location to load the target goods, and then arrive at a designated second target location to unload the loaded target goods.

[0088] Furthermore, the remote control center obtains a collaborative task and generates a collaborative instruction based on the collaborative task, including: the remote control center obtains the collaborative task by receiving input operations from a management user; calculates and processes the required number of collaborative robots based on the number of target goods in the collaborative task to obtain the number of collaborative robots required to be assigned to the collaborative task; and generates a collaborative instruction corresponding to the collaborative task based on the number of collaborative robots required to be assigned to the collaborative task.

[0089] Furthermore, the remote control center sorts the idle collaborative robots among the several collaborative robots according to the length of idle time and the length of time it takes for the collaborative robots in operation to complete the current collaborative tasks, and generates a collaborative task arrangement sorting list for the several collaborative robots; based on the number of collaborative robots required to be assigned to the collaborative task, a corresponding number of collaborative robots are selected from the collaborative task arrangement sorting list as multiple collaborative robots to perform collaborative tasks; the remote control center obtains multiple MAC addresses corresponding to the multiple collaborative robots to perform collaborative tasks, and generates collaborative instructions corresponding to the collaborative tasks based on the multiple MAC addresses.

[0090] Specifically, the remote control center obtains the collaborative task by receiving the input operation of the management user; the collaborative task is to arrive at the designated first target location to load the target goods, and then arrive at the designated second target location to unload the loaded target goods.

[0091] After obtaining the collaborative task, the required number of collaborative robots will be calculated based on the number of target goods in the collaborative task to obtain the number of collaborative robots required to be assigned to the collaborative task; then the collaborative instructions corresponding to the collaborative task will be generated based on the number of collaborative robots required to be assigned to the collaborative task.

[0092] The specific collaborative instructions are generated as follows: the remote control center sorts the idle collaborative robots among several collaborative robots according to the length of idle time and the time length for the collaborative robots in operation to complete the current collaborative tasks, and generates a collaborative task arrangement sorting list for several collaborative robots; then, according to the number of collaborative robots required to be assigned to the collaborative tasks, a corresponding number of collaborative robots are selected from the collaborative task arrangement sorting list as multiple collaborative robots to perform collaborative tasks; and the remote control center obtains multiple MAC addresses corresponding to the multiple collaborative robots to perform collaborative tasks, and finally generates collaborative instructions corresponding to the collaborative tasks through the multiple MAC addresses, and sends the collaborative instructions to the corresponding target collaborative robots.

[0093] Real-time acquisition module 302: used for the target collaborative robot to obtain the current operation area of ​​other collaborative robots shared by the remote control center in real time when receiving the collaborative instruction;

[0094] During the specific implementation of the present invention, when the target collaborative robot receives the collaborative instruction, it obtains the current working area of ​​other collaborative robots shared by the remote control center in real time, including: when the target collaborative robot receives the collaborative instruction, it generates a two-way communication instruction based on the collaborative instruction; the target collaborative robot establishes a two-way real-time communication channel with the remote control center during task execution based on the two-way communication instruction, and obtains the current working area of ​​other collaborative robots shared by the remote control center in real time based on the two-way real-time communication channel.

[0095] Specifically, when the target collaborative robot receives the collaborative instruction, it generates a two-way communication instruction based on the collaborative instruction; after obtaining the two-way communication instruction, the target collaborative robot will establish a two-way real-time communication channel with the remote control center during task execution through the two-way communication instruction, and at the same time obtain the current working area of ​​other collaborative robots shared by the remote control center in real time through the two-way communication channel.

[0096] Path planning module 303: used to perform path planning processing based on the current position of the target collaborative robot, the current working area of ​​other collaborative robots and the target position, and obtain the working planning path information of the target collaborative robot;

[0097] In the specific implementation process of the present invention, the path planning processing is performed based on the current position of the target collaborative robot, the working area of ​​other collaborative robots and the target position to obtain the working planning path information of the target collaborative robot, including: the target collaborative robot divides the current working area of ​​other collaborative robots into a non-drivable area; the target collaborative robot performs path planning processing based on the current position and the target position in a manner of avoiding the shortest driving path after the non-drivable area to obtain the working planning path information of the target collaborative robot.

[0098] Specifically, the target collaborative robot divides the current operating area of ​​other collaborative robots into a non-drivable area; then the target assisting robot will perform path planning processing according to the current position and the target position in a manner that avoids the shortest driving path after the non-drivable area, and obtain the operating planning path information of the target collaborative robot.

[0099] That is, the target collaborative robots are all connected to the remote control center through a wireless network, while each target collaborative robot is not directly connected to each other, because in a certain area of ​​the factory (target operation area), the use of a local area network can achieve the purpose of real-time information transmission, that is, by building a certain number of local area network devices (routers, etc.) in the factory, each robot can be connected to the remote control center; during the working process of the collaborative robot, people only need to send instructions to the collaborative robot at the remote control center. Generally, the robot starts from the initial position. Whenever the collaborative robot completes the previous task, if it does not receive a new task, it returns to the initial position and waits for new task instructions; but the collaborative robot supports receiving command strings, that is, accepting multiple commands at the same time. For example, a series of commands such as loading at a designated location and unloading at a designated location can be sent from the remote control center to the collaborative robot at the same time. The collaborative robot will recognize that it should go to the designated location to load first, and then It drives autonomously to the next designated location to unload. If a new instruction is received before unloading is completed, the collaborative robot will carry out the new instruction task after unloading is completed without returning to the original position. When receiving a new instruction, the collaborative robot will outline the working area (between the starting point and the end point) where the enterprise collaborative robot is located and the positions of other robots based on its own position and the position information of other collaborative robots received from the remote control center and the working area. For example, after a collaborative robot receives an instruction from the remote control center from the initial position, it obtains the target position point, and then calculates the robot's safe driving path based on the working area (non-drivable area, the positions of other robots), and outlines a regional path sequence (coordinate points, including horizontal and vertical coordinate points) to the target position from the initial position. This method uses the local area network for real-time information sharing, effectively avoids multi-robot congestion, and improves factory production efficiency.

[0100] Task execution module 304: used for the target collaborative robot to execute the collaborative task in the collaborative instruction based on the operation planning path information.

[0101] During the specific implementation of the present invention, the target collaborative robot executes the collaborative task in the collaborative instruction based on the operation planning path information, including: after controlling the target collaborative robot to reach the specified first target position based on the operation planning path information, controlling the robot grasping system to grasp the target cargo and place it in the robot cargo placement area; after completing the grasping of the target cargo, controlling the target collaborative robot to reach the second target position based on the operation planning path information, and controlling the robot grasping system to grasp the target cargo in the robot cargo placement area to complete the unloading operation.

[0102] Specifically, after controlling the target collaborative robot to reach the specified first target position through the operation planning path information, the robot grasping system is controlled to grasp the target goods and place them in the robot cargo placement area. After completing the grasping of the target goods, the target collaborative robot is controlled to reach the second target position through the operation planning path information, and the robot grasping system is controlled to grasp the target goods in the robot cargo placement area to complete the unloading operation; thereby completing the collaborative task in the collaborative instruction.

[0103] During the specific implementation of the present invention, executing collaborative tasks through job planning path information can avoid the congestion of multiple collaborative robots, thereby improving the work efficiency of multiple collaborative robots; that is, through real-time LAN communication between multiple collaborative robots and the remote control center, real-time data transmission is realized, and when planning and controlling, the global path information is combined to autonomously plan the robot's safe driving path to avoid congestion of multiple robots; through the all-round identification and grasping of the target goods by the robot grasping system of multiple collaborative robots, the object recognition accuracy is greatly enhanced, and the work efficiency of the collaborative robots is improved.

[0104] Example 4, please refer to Figure 4 , Figure 4 It is a schematic diagram of the structural composition of a multi-scenario composite collaborative robot control system in an embodiment of the present invention.

[0105] like Figure 4 As shown, a multi-scenario composite collaborative robot control method system includes a plurality of collaborative robots 401 and a remote control center 403 arranged in an operation area, a plurality of local area network devices 402 are arranged in the operation area, and the plurality of collaborative robots 401 are communicatively connected with the remote control center 403 via the local area network devices 402; the system is configured to implement the multi-scenario composite collaborative robot control method as described in any one of the above.

[0106] A computer-readable storage medium provided in an embodiment of the present invention stores a computer program on the computer-readable storage medium, and when the program is executed by a processor, the multi-scenario composite collaborative robot control method of any one of the above embodiments is implemented. Wherein, the computer-readable storage medium includes but is not limited to any type of disk (including floppy disk, hard disk, optical disk, CD-ROM, and magneto-optical disk), ROM (Read-Only Memory), RAM (Random Access Memory), EPROM (Erasable Programmable Read-Only Memory), EEPROM (Electrically Erasable Programmable Read-Only Memory), flash memory, magnetic card or optical card. That is, the storage device includes any medium that can store or transmit information in a readable form by a device (for example, a computer, a mobile phone), which can be a read-only memory, a disk or an optical disk, etc.

[0107] An embodiment of the present invention further provides a computer application that runs on a computer, and the computer application is used to execute the multi-scenario composite collaborative robot control method of any one of the above embodiments.

[0108] In addition, the above is a detailed introduction to a multi-scenario composite collaborative robot control method and related devices provided in an embodiment of the present invention. Specific examples are used herein to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea; at the same time, for general technical personnel in this field, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scopes. In summary, the content of this specification should not be understood as a limitation on the present invention.

Claims

1. A multi-scenario composite collaborative robot control method, characterized in that: Applied to a plurality of collaborative robots, the plurality of collaborative robots are connected to a remote control center for communication, the collaborative robots are composed of a robot walking system, a robot cargo placement area, and a robot grasping system; the method comprises: The remote control center obtains a collaborative task, generates a collaborative instruction based on the collaborative task, and sends the collaborative instruction to the corresponding target collaborative robot, wherein the collaborative instruction includes a target position of the collaborative task; When the target collaborative robot receives the collaborative instruction, it obtains the current operation area of ​​other collaborative robots shared by the remote control center in real time; Execute path planning processing based on the current position of the target collaborative robot, the current working area of ​​other collaborative robots and the target position to obtain the working planning path information of the target collaborative robot; The target collaborative robot executes the collaborative task in the collaborative instruction based on the operation planning path information.

2. The multi-scenario composite collaborative robot control method according to claim 1, characterized in that: The collaborative task is to arrive at a designated first target location to load the target goods, and then arrive at a designated second target location to unload the loaded target goods.

3. The multi-scenario composite collaborative robot control method according to claim 1, characterized in that: The remote control center obtains a collaborative task, and generates a collaborative instruction based on the collaborative task, including: The remote control center obtains the collaborative task by receiving an input operation of a management user; Calculate the number of collaborative robots required based on the number of target goods in the collaborative task to obtain the number of collaborative robots required to be allocated for the collaborative task; A collaboration instruction corresponding to the collaboration task is generated based on the number of collaborative robots required to be assigned to the collaboration task.

4. The multi-scenario composite collaborative robot control method according to claim 3 is characterized in that: The generating of the collaboration instruction corresponding to the collaboration task based on the number of collaborative robots required to be allocated to the collaboration task includes: The remote control center sorts the idle collaborative robots among the plurality of collaborative robots according to the length of idle time and the length of time until the collaborative robots in operation complete the current collaborative task, and generates a sorted list of collaborative task arrangements for the plurality of collaborative robots; Based on the number of collaborative robots required to be assigned to the collaborative task, a corresponding number of collaborative robots are selected from the collaborative task arrangement sorting list as a plurality of collaborative robots to be executed for the collaborative task; The remote control center obtains multiple MAC addresses corresponding to multiple collaborative robots to perform collaborative tasks, and generates collaborative instructions corresponding to the collaborative tasks based on the multiple MAC addresses.

5. The multi-scenario composite collaborative robot control method according to claim 1, characterized in that: When the target collaborative robot receives the collaborative instruction, it obtains the current operation area of ​​other collaborative robots shared by the remote control center in real time, including: When the target collaborative robot receives the collaborative instruction, generating a two-way communication instruction based on the collaborative instruction; The target collaborative robot establishes a two-way real-time communication channel with the remote control center during task execution based on the two-way communication instruction, and obtains the current working area of ​​other collaborative robots shared by the remote control center in real time based on the two-way real-time communication channel.

6. The multi-scenario composite collaborative robot control method according to claim 1, characterized in that: The performing path planning process based on the current position of the target collaborative robot, the operation areas of other collaborative robots, and the target position to obtain the operation planning path information of the target collaborative robot includes: The target collaborative robot divides the current operation area of ​​other collaborative robots into a non-drivable area; The target collaborative robot performs path planning processing based on the current position and the target position in a manner of the shortest driving path after avoiding the non-drivable area, and obtains the operation planning path information of the target collaborative robot.

7. The multi-scenario composite collaborative robot control method according to claim 1, characterized in that: The target collaborative robot executes the collaborative task in the collaborative instruction based on the operation planning path information, including: After controlling the target collaborative robot to reach a specified first target position based on the operation planning path information, controlling the robot grasping system to grasp the target cargo and place it in the robot cargo placement area; After completing the grabbing of the target cargo, the target collaborative robot is controlled to reach the second target position based on the operation planning path information, and the robot grabbing system is controlled to grab the target cargo in the robot cargo placement area to complete the unloading operation.

8. A multi-scenario composite collaborative robot control device, characterized in that: Applied to several collaborative robots, several of which are connected to a remote control center for communication. The collaborative robots are composed of three parts: a robot walking system, a robot cargo placement area, and a robot grasping system. The device includes: Sending module: used for the remote control center to obtain the collaborative task, generate a collaborative instruction based on the collaborative task, and send the collaborative instruction to the corresponding target collaborative robot, wherein the collaborative instruction includes the target position of the collaborative task; Real-time acquisition module: used for the target collaborative robot to obtain the current operation area of ​​other collaborative robots shared by the remote control center in real time when receiving the collaborative instruction; Path planning module: used to perform path planning processing based on the current position of the target collaborative robot, the current working area of ​​other collaborative robots and the target position, and obtain the working planning path information of the target collaborative robot; Task execution module: used for the target collaborative robot to execute the collaborative task in the collaborative instruction based on the operation planning path information.

9. A multi-scenario composite collaborative robot control method system, characterized in that: The system includes several collaborative robots and a remote control center arranged in a working area. Multiple local area network devices are arranged in the working area. Several collaborative robots are communicatively connected to the remote control center through the local area network devices. The system is configured to implement a multi-scenario composite collaborative robot control method as described in any one of claims 1 to 7.

10. A computer-readable storage medium for storing a computer program or code, characterized in that: When the computer program or code is executed by a processor, the multi-scenario composite collaborative robot control method as described in any one of claims 1 to 7 is implemented.

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