A composite robot control method, device, equipment and storage medium

Abstract

The present invention discloses a composite robot control method, apparatus, device, and storage medium. The method includes receiving target position information for the composite robot from a scheduling system; determining joint control information corresponding to the composite robot based on the target position information and a target controller in the composite robot, wherein the target controller includes at least one hierarchical controller that includes a hierarchical optimization algorithm; and controlling each mechanical joint of the composite robot based on the joint control information to solve the coordinated control problem of the chassis and the robotic arm through hierarchical optimization, effectively addressing technical issues at different time scales, and reducing the complexity and computational burden of the overall control of the composite robot.

Description

Technical Field

[0001] The present invention relates to the field of robot control technology, and in particular to a composite robot control method, device, equipment and storage medium. Background Art

[0002] A composite robot is a new type of robot that integrates the functions of a mobile robot and an industrial robot. It is generally composed of an autonomous mobile chassis, a robotic arm, vision and an end effector.

[0003] Existing hybrid robot motion planning and control technologies can be broadly categorized into two approaches: 1. Separate control of the manipulator arm and chassis; 2. Joint control of the manipulator arm and chassis. Separate control splits the hybrid robot's operation task into chassis and manipulator tasks, calculating the target motion trajectories for each based on their kinematic / dynamic models. These are then controlled separately through separate controllers. Joint control treats the chassis and manipulator arm as a single entity, establishing a kinematic / dynamic model for the hybrid robot. A single controller then uniformly solves for the target motion trajectories and control inputs for all joints of the manipulator arm and chassis, achieving integrated control.

[0004] However, independent control cannot fully utilize the redundant degrees of freedom of a composite robot, resulting in disconnected movements of the "hands and feet," decreased tempo, and difficulty completing complex tasks. Joint control is difficult to model and solve, requiring high computing power. Furthermore, because the control frequency requirements of the chassis and robotic arm differ significantly (typically in the kHz range for robotic arms and 20-50Hz for chassis), it is difficult to accommodate both timescales using the same controller. Consequently, existing control technologies cannot meet the demands of practical applications. Summary of the Invention

[0005] The present invention provides a composite robot control method, device, equipment and storage medium, which solve the collaborative control problem of the chassis and robotic arm through hierarchical optimization, effectively handle technical problems at different time scales, and reduce the complexity and computational burden of the overall control of the composite robot.

[0006] According to one aspect of the present invention, a method for controlling a composite robot is provided. The method comprises:

[0007] Receive the target position information of the composite robot sent by the scheduling system;

[0008] Determining joint control information corresponding to the compound robot according to the target position information and a target controller in the compound robot, wherein the target controller includes at least one hierarchical controller, and the hierarchical controller includes a hierarchical optimization algorithm;

[0009] Control processing is performed on each mechanical joint of the compound robot according to the joint control information.

[0010] According to another aspect of the present invention, a composite robot control device is provided. The device comprises:

[0011] The target position information receiving module is used to receive the target position information of the composite robot sent by the scheduling system;

[0012] a joint control information determination module, configured to determine joint control information corresponding to the compound robot based on the target position information and a target controller in the compound robot, wherein the target controller includes at least one hierarchical controller, and the hierarchical controller includes a hierarchical optimization algorithm;

[0013] The composite robot control module is used to control and process each mechanical joint of the composite robot according to the joint control information.

[0014] According to another aspect of the present invention, an electronic device is provided, comprising:

[0015] at least one processor; and

[0016] a memory communicatively connected to the at least one processor; wherein,

[0017] The memory stores a computer program that can be executed by the at least one processor. The computer program is executed by the at least one processor to enable the at least one processor to execute the composite robot control method according to any embodiment of the present invention.

[0018] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the composite robot control method according to any embodiment of the present invention when executed.

[0019] The technical solution of an embodiment of the present invention receives target position information for a composite robot from a scheduling system. Based on this target position information and a target controller in the composite robot, joint control information corresponding to the composite robot is determined. Based on this joint control information, each mechanical joint of the composite robot is controlled and processed. This solves the problem of coordinated control of the chassis and robotic arm at different time scales. Global control information for the chassis and robotic arm is determined through hierarchical optimization, reducing the overall control complexity and computational burden of the composite robot and improving the adaptability and robustness of the composite robot's control.

[0020] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present invention, nor is it intended to limit the scope of the present invention. Other features of the present invention will become readily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. 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 creative work.

[0022] Figure 1 is a flow chart of a composite robot control method provided according to an embodiment of the present invention;

[0023] Figure 2 is a structural diagram of a composite robot control device provided according to an embodiment of the present invention;

[0024] Figure 3 It is a schematic structural diagram of an electronic device for implementing the composite robot control method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0025] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described 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 making creative efforts should fall within the scope of protection of the present invention.

[0026] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0027] Figure 1 This is a flow chart of a composite robot control method provided by the present invention. This embodiment is applicable to the case of precisely controlling a composite robot. This method can be executed by a composite robot control device. The composite robot control device can be implemented in the form of hardware and / or software. The composite robot control device can be configured in an electronic device. Figure 1 As shown, the method includes:

[0028] S101, receiving target position information of the composite robot to be reached from the scheduling system.

[0029] The scheduling system may refer to a host computer capable of controlling the composite robot, such as a control server, etc. The target position information may refer to the final position to be reached by the chassis and the manipulator arm of the composite robot.

[0030] Specifically, the target location information sent by the scheduling system is received according to an effective communication channel between the composite robot and the scheduling system. Exemplarily, the communication channel may include but is not limited to Wi-Fi, 4G / 5G, Bluetooth or other dedicated communication channels.

[0031] S102 : Determine joint control information corresponding to the compound robot according to the target position information and a target controller in the compound robot.

[0032] Among them, the target controller includes at least one hierarchical controller, the hierarchical controller includes a hierarchical optimization algorithm, and the joint control information may refer to the control information for regulating each joint of the composite robot. For example, the joint control information may be joint torque control information or joint current control information, etc.

[0033] It should be noted that the number of hierarchical controllers in the target controller can be increased or decreased as needed, and the objective function, optimization object and constraint conditions of each hierarchical controller can be defined as needed.

[0034] Specifically, the motion planning and control problem of the composite robot is decomposed into one or more manageable levels through the target controller, and the corresponding joint control information of the composite robot is calculated through the hierarchical optimization algorithm in the hierarchical controller.

[0035] Exemplarily, the target controller can be specifically divided into an upper-layer controller, a middle-layer controller and a lower-layer controller, wherein the upper-layer controller includes an upper-layer optimization algorithm, the middle-layer controller includes a middle-layer optimization algorithm, and the lower-layer controller includes a lower-layer optimization algorithm.

[0036] Exemplarily, the method of determining the joint control information corresponding to the composite robot based on the target position information and the target controller in the composite robot includes: sending the target position information to the upper-level controller, and obtaining the overall position-velocity matrix of the chassis and the end of the robotic arm output by the upper-level controller based on the upper-level optimization algorithm and the upper-level constraint conditions in the upper-level controller; sending the overall position-velocity matrix of the chassis and the end of the robotic arm to the middle-level controller, and obtaining the joint position-velocity matrix of the chassis and the robotic arm output by the middle-level controller based on the middle-level optimization algorithm and the middle-level constraint conditions in the middle-level controller; sending the joint position-velocity matrix to the lower-level controller, and obtaining the joint control information output by the lower-level controller based on the lower-level optimization algorithm and the lower-level constraint conditions in the lower-level controller.

[0037] It should be noted that each level of optimization algorithm includes at least one constraint. The constraint conditions of the upper-level optimization algorithm include at least that the distance between the chassis of the composite robot and the obstacle is greater than or equal to a preset distance threshold, the operating speed of the chassis and the manipulator of the composite robot is less than or equal to a preset speed threshold, and the manipulator finally reaches the target position; the constraint conditions of the middle-level optimization algorithm include at least that the positions of the joints of the composite robot are within a preset position interval, the operating speed of each joint is within a preset operating speed interval, the distance between the chassis and the manipulator is within a preset safety distance interval, and the manipulator is prohibited from entering a singular posture; the constraint conditions of the lower-level optimization algorithm include at least that the control input of each joint is within a preset safety control interval, and the control stability value is greater than or equal to the minimum stability value. The constraint conditions of each level can be used to constrain the output results of each level to ensure the safety and accuracy of the joint control information.

[0038] The overall position-velocity matrix can describe the position and velocity matrix of the chassis and the end of the manipulator in the composite robot. For example, the overall position-velocity matrix can include the output chassis position information, output chassis velocity information, output end position information, and output end velocity information output by the upper-level controller. The joint position-velocity matrix can describe the position and velocity matrix of each joint in the composite robot. For example, the joint position-velocity matrix can include the output joint angle information and output joint angular velocity information output by the middle-level controller.

[0039] Specifically, the upper-level controller is used to handle global optimization problems on a larger time scale, such as path planning, energy consumption management, etc. The upper-level controller calculates the overall position-velocity matrix based on the target position information sent by the scheduling system, through the upper-level optimization algorithm and the upper-level constraints, and then sends it to the middle-level controller. The middle-level controller is used to handle the coordination problem of the chassis and the robotic arm to ensure that the control instructions sent by the upper-level controller are accurately executed. The middle-level controller receives the overall position-velocity matrix sent by the upper-level controller, and based on the kinematics and / or dynamics model of the composite robot, calculates the joint position-velocity matrix corresponding to each joint of the chassis and the robotic arm through the middle-level optimization algorithm and the middle-level constraints, and then sends it to the bottom-level controller. The lower-level controller is used to track the joint position-velocity matrix sent by the middle-level controller in real time, and obtain the joint control information of each joint through the lower-level optimization algorithm and the lower-level constraints.

[0040] Exemplarily, the upper layer optimization algorithm includes:

[0041]

[0042] Among them, J High represents the upper objective function, μ high Represents the overall position-velocity matrix output by the upper controller;

[0043] Accordingly, the upper layer objective function includes:

[0044]

[0045] Among them, k represents the number of time steps, N high Indicates the total time step, x goal Indicates the target location information, x base,ref(k) Indicates the chassis target position output by the upper controller, x arm,ref Represents the end position of the manipulator output by the upper controller, R high Represents the weight matrix corresponding to the upper control input, α1-α4 represents the four weight coefficients, ObstacleCost() is a function describing the obstacle distance, μ high (k) represents the overall position velocity matrix output by the upper controller, x ob (k) represents the obstacle location information.

[0046] It should be noted that in the upper-level target optimization algorithm, the first and second parts reflect the deviation of the chassis and robotic arm relative to the target position information, the third part reflects the energy consumption of the system, and the fourth part reflects the risk of collision between the robot and environmental obstacles.

[0047] For example, μ high is defined as:

[0048] μ high =(x base,ref ,x arm,ref ,v base,ref ,v arm,ref ) T ;

[0049] Among them, x base,ref Indicates the chassis target position output by the upper controller, x arm,ref represents the target position of the end of the manipulator output by the upper controller, v base,ref It can refer to the chassis target speed output by the upper controller, v arm,ref It can refer to the target speed of the robot arm output by the upper controller.

[0050] For example, upper-level constraints include but are not limited to:

[0051] 1) The distance between the chassis and the obstacle must not be less than a certain threshold, that is

[0052]

[0053] Among them, x base,ref(k) represents the output chassis position of the upper controller output chassis, i represents the number of the obstacle, and x_ob,i(k) represents the obstacle position information.

[0054] 2) The speed of the chassis and the robotic arm must not exceed the maximum value allowed by the system, that is:

[0055] ||v base,ref (k)||≤v max,base ;||v arm,ref (k)||≤v max,arm ;

[0056] v base,ref (k) can refer to the chassis target speed output by the upper controller, v arm,ref (k) can refer to the target speed of the robot arm output by the upper controller.

[0057] 3) The robotic arm finally reaches the target position, i.e.

[0058] x arm，ref (N high )=x goal ;

[0059] x arm,ref Indicates the output end position of the upper controller outputting the end of the manipulator, N high Indicates the total time step, x goal Indicates target location information.

[0060] Exemplarily, the middle-level optimization algorithm includes:

[0061]

[0062] Among them, J Mid represents the middle-level objective function, μ mid Represents the joint position velocity matrix output by the middle-level controller;

[0063] Accordingly, the middle-level objective function includes:

[0064]

[0065] Among them, k represents the number of time steps, N mid Indicates the total time step, R mid Represents the weight matrix corresponding to the middle-level control input, x base Indicates the current chassis position, x arm Indicates the current end position of the robotic arm, x base,ref(k) Indicates the chassis target position output by the upper controller, x arm,ref represents the target position of the end of the manipulator output by the upper controller, β1-β4 represent 4 weight coefficients, μ mid Represents the joint position velocity matrix output by the middle-level controller, C coord () describes the coordination function between chassis and robotic arm, q ref Represents the target angle of each joint output by the middle-level controller.

[0066] For example, μ mid is defined as:

[0067]

[0068] Among them, q ref represents the target angle of each joint output by the middle-level controller, It indicates that the middle-level controller outputs the output joint angular velocity of each joint.

[0069] It should be noted that in the middle-level objective function algorithm, the first and second parts reflect the deviation of the chassis and the manipulator relative to the target position information, the third part reflects the energy consumption of each joint, and the fourth part C coord () is an indicator that reflects the degree of coordination between the chassis and the robotic arm, and is related to the posture of the robotic arm and the chassis.

[0070] For example, the middle-level constraints include but are not limited to:

[0071] 1) Position and speed limits of the chassis and robotic arm joints, namely:

[0072]

[0073] Among them, i represents the joint number, q represents the joint angle, Represents angular velocity.

[0074] 2) The distance between the chassis and the robotic arm must be within a safe range and no collision should occur, that is:

[0075]

[0076] Among them, x base Indicates the current chassis position, x arm Indicates the current arm position at the end of the arm.

[0077] 3) The robotic arm must not enter a strange position.

[0078] Exemplarily, the lower layer optimization algorithm includes:

[0079]

[0080] Among them, J Low represents the lower layer objective function, μ low Represents the joint control information output by the lower controller;

[0081] Accordingly, the lower layer objective function includes:

[0082]

[0083] Among them, k represents the number of time steps, N low represents the total time step, q represents the joint angle, represents the angular velocity, q ref represents the target angle of each joint output by the middle-level controller, Represents the target angular velocity of each joint output by the middle-level controller, μ low represents the joint control information output by the lower-layer controller, and Y1-Y3 represent three weight coefficients.

[0084] It should be noted that in the lower-level objective optimization algorithm, the first and second parts reflect the tracking errors of each joint trajectory, and the third part reflects the energy consumption of each actuator.

[0085] For example, the lower-level constraints include but are not limited to:

[0086] 1) The control input of each joint must not exceed the maximum value allowed by the system. If the control input is torque, then:

[0087]

[0088] Where i represents the joint number, μlow Represents the joint control information output by the lower-layer controller.

[0089] 2) System stability constraint, that is, the system stability threshold must be greater than its minimum value,

[0090]

[0091] For example, the overturning moment of a composite robot can be used to calculate the system stability threshold. Overturning moment refers to the moment that causes the composite robot to overturn along a specific axis during operation due to changes in its center of gravity and load, acceleration / deceleration, and environmental interaction forces. The greater the overturning moment, the worse the stability.

[0092] S103 : Control each mechanical joint of the compound robot according to the joint control information.

[0093] Specifically, the joint control information is sent to each joint servo driver of the compound robot, and then the control processing of each mechanical joint of the compound robot is realized according to the joint control information.

[0094] The technical solution of an embodiment of the present invention receives target position information for a composite robot from a scheduling system. Based on this target position information and a target controller in the composite robot, joint control information corresponding to the composite robot is determined. Based on this joint control information, each mechanical joint of the composite robot is controlled and processed. This solves the problem of coordinated control of the chassis and robotic arm at different time scales. Global control information for the chassis and robotic arm is determined through hierarchical optimization, reducing the overall control complexity and computational burden of the composite robot and improving the adaptability and robustness of the composite robot's control.

[0095] Based on the above embodiments, the method further includes:

[0096] Acquiring operating parameter information of the composite robot based on the lower-layer controller, and sending the operating parameter information to the middle-layer controller, wherein the operating parameter information includes at least measurement values such as joint position information, velocity information, acceleration information, and torque;

[0097] Determining operation safety information of the composite robot based on the operation parameter information received by the middle-level controller, and sending the operation safety information to the upper-level controller, wherein the operation safety information includes at least global positioning information and environmental obstacle distance information;

[0098] Based on the operation safety information received by the upper controller, the task execution status of the compound robot is determined, and the task execution status is fed back to the scheduling system.

[0099] That is, the lower-level controller collects operational parameter information of the composite robot, such as joint position, velocity, acceleration, and torque measurements, based on sensor feedback, and sends this operational parameter information to the middle-level controller. Based on the feedback from the lower-level controller, the middle-level controller calculates operational safety information such as the composite robot's global positioning and the distance to environmental obstacles, and returns this information to the upper-level controller. The upper-level controller determines the status of task execution based on the operational safety information fed back by the middle-level controller and reports it to the scheduling system. The lower-level controller can quickly respond to interference (such as obstacles, slippage, etc.) and provide feedback to the upper-level controller, prompting it to adjust its strategy or goals to ensure that the system can operate robustly in a dynamic and uncertain environment. At the same time, the lower-level controller can detect the deviation between the actual trajectory and the target trajectory in real time, adjust the control action, and feed these changes back to the upper-level controller for re-optimization, which helps to quickly correct errors.

[0100] The present invention adopts a hierarchical optimization control architecture to decompose the problem of whole-body motion planning and control of a complex composite robot into multiple sub-problems and solve them layer by layer. The high-level controller is used to handle global optimization problems of large event scales (such as global path planning), and the low-level controller is used to handle local optimization problems of small time scales (such as joint trajectory tracking). The controllers at each level work together, with the high-level controller providing control target values and constraints to the low-level controller, and the low-level controller providing execution result feedback to the high-level co-controller. The controllers at each level can run at different frequencies to maximize the use of computing resources.

[0101] Figure 2 This is a schematic diagram of the structure of a composite robot control device provided by the present invention. Figure 2 As shown, the device includes:

[0102] The target position information receiving module 301 is used to receive the target position information of the composite robot to be reached sent by the scheduling system;

[0103] a joint control information determining module 302 for determining joint control information corresponding to the composite robot based on the target position information and a target controller in the composite robot, wherein the target controller includes at least one hierarchical controller, and the hierarchical controller includes a hierarchical optimization algorithm;

[0104] The compound robot control module 303 is used to control each mechanical joint of the compound robot according to the joint control information.

[0105] The technical solution of the present invention receives target position information for a composite robot from a scheduling system. Based on this target position information and the target controller in the composite robot, it determines the corresponding joint control information for the composite robot. Based on this joint control information, it controls and processes each mechanical joint of the composite robot. This addresses the issue of differing time scales between the chassis and the robotic arm. Global control information for the chassis and robotic arm is determined by layering the task hierarchy, reducing the overall control complexity and computational burden of the composite robot and improving the adaptability and robustness of the composite robot's control.

[0106] Optionally, the target controller includes an upper-layer controller, a middle-layer controller and a lower-layer controller; the upper-layer controller includes an upper-layer optimization algorithm, the middle-layer controller includes a middle-layer optimization algorithm, and the lower-layer controller includes a lower-layer optimization algorithm.

[0107] Optionally, the joint control information determination module 302 is specifically configured to:

[0108] The target position information is sent to the upper controller, and based on the upper optimization algorithm and upper constraint conditions in the upper controller, the overall position velocity matrix of the chassis and the end of the manipulator output by the upper controller is obtained;

[0109] Sending the overall position-velocity matrix of the chassis and the end of the robotic arm to the middle-level controller, and obtaining the joint position-velocity matrix of the chassis and the end of the robotic arm output by the middle-level controller based on the middle-level optimization algorithm and middle-level constraints in the middle-level controller;

[0110] The joint position velocity matrix is sent to the lower-layer controller, and based on the lower-layer optimization algorithm and lower-layer constraint conditions in the lower-layer controller, the joint control information output by the lower-layer controller is obtained.

[0111] Optionally, the upper layer optimization algorithm includes:

[0112]

[0113] Among them, J High represents the upper objective function, μ high Represents the overall position-velocity matrix output by the upper controller;

[0114] Accordingly, the upper layer objective function includes:

[0115]

[0116] Among them, k represents the number of time steps, N high Indicates the total time step, x goal Indicates the target location information, xbase,ref(k) Indicates the chassis target position output by the upper controller, x arm,ref Represents the end position of the manipulator output by the upper controller, R high Represents the weight matrix corresponding to the upper control input, α1-α4 represents the four weight coefficients, ObstacleCost() is a function describing the obstacle distance, μ high (k) represents the overall position velocity matrix output by the upper controller, x ob (k) represents the obstacle location information.

[0117] Optionally, the mid-level optimization algorithm includes:

[0118]

[0119] Among them, J Mid represents the middle-level objective function, μ mid Represents the joint position velocity matrix output by the middle-level controller;

[0120] Accordingly, the middle-level objective function includes:

[0121]

[0122] Among them, k represents the number of time steps, N mid Indicates the total time step, R mid Represents the weight matrix corresponding to the middle-level control input, x base Indicates the current chassis position, x arm Indicates the current end position of the robotic arm, x base,ref(k) Indicates the chassis target position output by the upper controller, x arm,ref represents the target position of the end of the manipulator output by the upper controller, β1-β4 represent 4 weight coefficients, μ mid Represents the joint position velocity matrix output by the middle-level controller, C coord () describes the coordination function between chassis and robotic arm, q ref Represents the target angle of each joint output by the middle-level controller.

[0123] Optionally, the lower layer optimization algorithm includes:

[0124]

[0125] Among them, J Low represents the lower layer objective function, μ low Represents the joint control information output by the lower controller;

[0126] Accordingly, the lower layer objective function includes:

[0127]

[0128] Among them, k represents the number of time steps, N low represents the total time step, q represents the joint angle, represents the angular velocity, q ref represents the target angle of each joint output by the middle-level controller, Represents the target angular velocity of each joint output by the middle-level controller, μ low represents the joint control information output by the lower-layer controller, and Y1-Y3 represent three weight coefficients.

[0129] Optionally, the device further includes an information feedback module.

[0130] The information feedback module is used to:

[0131] Acquiring operating parameter information of the composite robot based on the lower-layer controller, and sending the operating parameter information to the middle-layer controller, wherein the operating parameter information includes at least measurement values such as joint position information, velocity information, acceleration information, and torque;

[0132] Determining operation safety information of the composite robot based on the operation parameter information received by the middle-level controller, and sending the operation safety information to the upper-level controller, wherein the operation safety information includes at least global positioning information and environmental obstacle distance information;

[0133] Based on the operation safety information received by the upper controller, the task execution status of the compound robot is determined, and the task execution status is fed back to the scheduling system.

[0134] The composite robot control device provided by the embodiment of the present invention can execute the composite robot control method provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0135] Figure 3 A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or claimed herein.

[0136] like Figure 3 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., which is communicatively connected to the at least one processor 11. The memory stores a computer program that can be executed by the at least one processor. The processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 into the random access memory (RAM) 13. Various programs and data required for the operation of the electronic device 10 can also be stored in the RAM 13. The processor 11, ROM 12, and RAM 13 are connected to each other via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0137] Multiple components in the electronic device 10 are connected to the I / O interface 15, including an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a magnetic disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0138] The processor 11 may be any general-purpose and / or specialized processing component with processing and computing capabilities. Examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various specialized artificial intelligence (AI) computing chips, various processors for running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as the method for complex robot control.

[0139] In some embodiments, the method for complex robotic control can be implemented as a computer program tangibly embodied in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the method for complex robotic control described above can be performed. Alternatively, in other embodiments, processor 11 can be configured to perform the method for complex robotic control in any other suitable manner (e.g., via firmware).

[0140] Various embodiments of the systems and techniques described herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), system-on-chip systems (SOCs), programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include being implemented in one or more computer programs that are executable and / or interpreted on a programmable system that includes at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0141] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when the computer program is executed by the processor, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The computer program may be executed entirely on the machine, partially on the machine, as a stand-alone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0142] In the context of the present invention, computer-readable storage media can be tangible media that can contain or store a computer program for use with an instruction execution system, device or equipment or used in combination with an instruction execution system, device or equipment. Computer-readable storage media can include but are not limited to electronic, magnetic, optical, electromagnetic, infrared or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, computer-readable storage media can be machine-readable signal media. More specific examples of machine-readable storage media can include electrical connections based on one or more lines, portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0143] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0144] The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0145] A computing system may include clients and servers. The clients and servers are typically remote from each other and typically interact via a communication network. This client-server relationship arises through computer programs running on the respective computers, creating a client-server relationship. The server may be a cloud server, also known as a cloud computing server or cloud host. This server is a hosting product within the cloud computing service ecosystem that addresses the management difficulties and limited scalability of traditional physical hosting and VPS services.

[0146] It should be understood that the various forms of the processes shown above can be used to reorder, add, or delete steps. For example, the steps described in the present invention can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solution of the present invention can be achieved. This is not limited herein.

[0147] The above specific embodiments do not limit the scope of protection of the present invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention are intended to be included within the scope of protection of the present invention.

Claims

1. A composite robot control method, characterized in that: include: Receive the target position information of the composite robot sent by the scheduling system; Determining joint control information corresponding to the compound robot according to the target position information and a target controller in the compound robot, wherein the target controller includes at least one hierarchical controller, the hierarchical controller includes a hierarchical optimization algorithm, the target controller includes an upper-layer controller, a middle-layer controller, and a lower-layer controller; the upper-layer controller includes an upper-layer optimization algorithm, the middle-layer controller includes a middle-layer optimization algorithm, and the lower-layer controller includes a lower-layer optimization algorithm; performing control processing on each mechanical joint of the compound robot according to the joint control information; Determining joint control information corresponding to the compound robot according to the target position information and a target controller in the compound robot includes: The target position information is sent to the upper controller, and based on the upper optimization algorithm and upper constraint conditions in the upper controller, the overall position velocity matrix of the chassis and the end of the manipulator output by the upper controller is obtained; Sending the overall position-velocity matrix of the chassis and the end of the robotic arm to the middle-level controller, and obtaining the joint position-velocity matrix of the chassis and the robotic arm output by the middle-level controller based on the middle-level optimization algorithm and middle-level constraints in the middle-level controller; The joint position velocity matrix is sent to the lower-layer controller, and based on the lower-layer optimization algorithm and lower-layer constraint conditions in the lower-layer controller, the joint control information output by the lower-layer controller is obtained.

2. The method according to claim 1, characterized in that The upper layer optimization algorithm includes: ； in, represents the upper objective function, Represents the overall position-velocity matrix output by the upper controller; Accordingly, the upper layer objective function includes: ； in, represents the number of time steps, represents the total time step, Indicates the target location information, Indicates the chassis target position output by the upper controller, Indicates the end position of the manipulator output by the upper controller, Represents the weight matrix corresponding to the upper control input, Represents 4 weight coefficients, is a function describing the distance to the obstacle, represents the overall position-velocity matrix output by the upper controller, Indicates obstacle location information.

3. The method according to claim 1, characterized in that The middle-level optimization algorithm includes: ； in, represents the middle-level objective function, Represents the joint position velocity matrix output by the middle-level controller; Accordingly, the middle-level objective function includes: ； in, represents the number of time steps, represents the total time step, represents the weight matrix corresponding to the middle-level control input, Indicates the current chassis position, Indicates the current end position of the robotic arm. Indicates the chassis target position output by the upper controller, Indicates the target position of the end of the manipulator output by the upper controller, Represents 4 weight coefficients, represents the joint position velocity matrix output by the middle-level controller, Describe the function of the degree of coordination between the chassis and the robotic arm, Represents the target angle of each joint output by the middle-level controller.

4. The method according to claim 1, wherein The lower layer optimization algorithm includes: ； in, represents the lower layer objective function, Represents the joint control information output by the lower controller; Accordingly, the lower layer objective function includes: ； in, represents the number of time steps, represents the total time step, Indicates joint angle, represents the angular velocity, represents the target angle of each joint output by the middle-level controller, represents the target angular velocity of each joint output by the middle-level controller, represents the joint control information output by the lower controller, Represents 3 weight coefficients.

5. The method according to claim 1, characterized in that The method further comprises: Acquiring operating parameter information of the composite robot based on the lower-layer controller, and sending the operating parameter information to the middle-layer controller, wherein the operating parameter information includes at least joint position information, velocity information, acceleration information, and torque measurement values; Determining operation safety information of the composite robot based on the operation parameter information received by the middle-level controller, and sending the operation safety information to the upper-level controller, wherein the operation safety information includes at least global positioning information and environmental obstacle distance information; Based on the operation safety information received by the upper controller, the task execution status of the compound robot is determined, and the task execution status is fed back to the scheduling system.

6. A composite robot control device, characterized in that: include: The target position information receiving module is used to receive the target position information of the composite robot sent by the scheduling system; a joint control information determination module, configured to determine joint control information corresponding to the compound robot based on the target position information and a target controller in the compound robot, wherein the target controller includes at least one hierarchical controller, the hierarchical controller includes a hierarchical optimization algorithm, the target controller includes an upper-layer controller, a middle-layer controller, and a lower-layer controller; the upper-layer controller includes an upper-layer optimization algorithm, the middle-layer controller includes a middle-layer optimization algorithm, and the lower-layer controller includes a lower-layer optimization algorithm; A composite robot control module, configured to control each mechanical joint of the composite robot according to the joint control information; The joint control information determination module is specifically used to: The target position information is sent to the upper controller, and based on the upper optimization algorithm and upper constraint conditions in the upper controller, the overall position velocity matrix of the chassis and the end of the manipulator output by the upper controller is obtained; Sending the overall position-velocity matrix of the chassis and the end of the robotic arm to the middle-level controller, and obtaining the joint position-velocity matrix of the chassis and the end of the robotic arm output by the middle-level controller based on the middle-level optimization algorithm and middle-level constraints in the middle-level controller; The joint position velocity matrix is sent to the lower-layer controller, and based on the lower-layer optimization algorithm and lower-layer constraint conditions in the lower-layer controller, the joint control information output by the lower-layer controller is obtained.

7. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor. The computer program is executed by the at least one processor to enable the at least one processor to perform the composite robot control method according to any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the composite robot control method according to any one of claims 1 to 5 when executed.

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