Composite robot integrated controller, electronic equipment, robot and storage medium

By introducing an integrated design of a main control unit and a heterogeneous safety module into the composite robot system, the problem of the disconnect between the control of the robotic arm and the chassis is solved, achieving efficient collaborative execution and real-time safety defense, and improving the stability and safety of the system.

CN120941415AActive Publication Date: 2025-11-14SUZHOU ELITE ROBOTICS CO LTD +1
View PDF 6 Cites 0 Cited by

Patent Information

Application Number
CN202511472853.X
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-10-15
Publication Date
2025-11-14
Estimated Expiration
2045-10-15

AI Technical Summary

Technical Problem

In existing composite robot systems, the control of the robotic arm and chassis is independent, safety functions rely on a single controller, and there is a lack of heterogeneous redundancy and real-time linkage. This results in complex coupling between modules, cumbersome wiring, high debugging costs, fragmented safety strategies with slow response, lack of environmental perception capabilities, heavy reliance on the main controller, and a lack of fault tolerance and prediction mechanisms.

Method used

The system employs a main control unit integrated on the same hardware platform and independent heterogeneous safety modules. The main control unit runs on a processor with real-time scheduling capabilities, integrating the perception, planning, and control logic of the robotic arm and chassis. The heterogeneous safety modules independently perform safety monitoring and protection functions through processors with different architectures. The main control unit and the heterogeneous safety modules achieve data interaction through physically isolated communication links, and achieve task isolation and shared memory communication in a lightweight Hypervisor virtualization environment.

Benefits of technology

It achieves efficient collaborative execution between the robotic arm and the chassis, improves the system's real-time response and safety assurance capabilities, and reduces the risk of collision and the possibility of fault expansion through dynamic safety zone calculation and fault diagnosis modules, thereby enhancing the operational stability and safety in complex industrial scenarios.

✦ Generated by Eureka AI based on patent content.

Smart Images

  • Figure CN120941415A_ABST
    Figure CN120941415A_ABST
Patent Text Reader

Abstract

The invention discloses an integrated controller of a composite robot. The integrated controller comprises a main control unit and an independent heterogeneous safety module which are integrated on the same hardware platform, the main control unit runs on a processor with real-time scheduling capability and is used for integrating sensing, planning and control logic of the mechanical arm and the chassis; the heterogeneous security module adopts a processor with a structure different from that of the main control unit and is used for independently executing security monitoring and protection functions; the main control unit and the heterogeneous security module realize data interaction through a physically isolated communication link, and security control logic and conventional control logic are separately deployed, so that the security response capability, task cooperation efficiency and system robustness of the composite robot in a complex industrial environment are improved.
Need to check novelty before this filing date? Find Prior Art

Description

Technical Field

[0001] This invention relates to the field of robotics, and more specifically, to a composite robot integrated controller, electronic device, robot, and storage medium. Background Technology

[0002] In the field of composite robots, the current design of controllers and safety strategies mostly adopts a distributed control architecture, that is, safety logic is deployed in the robotic arm controller and the chassis controller respectively: the robotic arm controller mainly relies on collision detection, speed / current monitoring, safety emergency stop and other modules to realize safety functions, while the chassis controller ensures safety through safety LiDAR, safety encoder, safety PLC and other modules. The linkage between the two is usually achieved through safety I / O or communication.

[0003] However, these safety systems share several significant common problems: First, they lack a unified controller architecture. Existing solutions generally employ a dual-controller + safety PLC architecture, which not only results in complex inter-module coupling, cumbersome wiring, and high debugging costs, but also poor collaborative emergency response capabilities. Second, safety strategies are fragmented and slow to react. The safety strategies of the robotic arm and the chassis are independent of each other. For example, when the chassis responds to the lidar emergency stop, the robotic arm may still be in motion, posing a collision risk. Furthermore, information transmission delays may also cause response lag. Third, safety boundaries are static and lack environmental awareness. The safety zones of most systems are statically configured parameters without real-time adjustment mechanisms, making it difficult to adapt to dynamic scenarios. Fourth, they are heavily reliant on the main controller and lack fault tolerance and prediction mechanisms. Regardless of whether the main controller is a robotic arm controller, chassis controller, or upper-level industrial PC, existing systems lack heterogeneous redundant paths to effectively determine whether the current state is safe and whether emergency protection mode needs to be entered in the event of calculation anomalies, communication interruptions, or task logic freezes. Summary of the Invention

[0004] To address the problems in existing composite robot systems, such as independent control of the robotic arm and chassis, reliance on a single controller for safety functions, and lack of heterogeneous redundancy and real-time linkage, this invention provides an integrated controller for composite robots, including a main control unit integrated on the same hardware platform and an independent heterogeneous safety module. The main control unit runs on a processor with real-time scheduling capabilities and is used to integrate the perception, planning and control logic of the robotic arm and the chassis. The heterogeneous security module uses a processor with a different architecture than the main control unit to independently perform security monitoring and protection functions; The main control unit and the heterogeneous security module interact with each other through physically isolated communication links, and the security control logic is deployed separately from the conventional control logic.

[0005] As a preferred technical solution, the main control unit constructs a virtualized operating environment through a lightweight hypervisor to achieve isolated operation of robotic arm control tasks and chassis control tasks, and low-latency data synchronization between tasks is achieved through shared memory.

[0006] As a preferred technical solution, the heterogeneous safety module includes a dynamic safety area calculation module. This unit generates a set of future positions of the robot body and surrounding obstacles by predicting them, and dynamically generates a three-dimensional safety area based on position uncertainty parameters, thereby realizing the linkage obstacle avoidance between the robotic arm and the chassis.

[0007] As a preferred technical solution, the dynamic safe area calculation module generates a three-dimensional safe area through the following steps: Real-time acquisition of the current motion status information of the robot body and surrounding obstacles, including position, velocity and acceleration; Predict the trajectory of the robot and obstacles in the future and simultaneously calculate the uncertainty of its position prediction; Based on the uncertainty covariance of the position prediction, the safety expansion radius is calculated, and the physical structure dimensions of the robot are expanded in real time to generate a three-dimensional safety area that adapts to the motion state. The robot continuously detects whether the predicted trajectory of an obstacle intersects with the three-dimensional safe area. If an intrusion occurs, the robot's cooperative obstacle avoidance or emergency braking strategy is triggered.

[0008] As a preferred technical solution, the real-time expansion of the robot's physical structure to generate a three-dimensional safety region that adaptively changes with the motion state includes: Safety zones are constructed for the chassis and the robotic arm respectively. The chassis safety zone is constructed using a cuboid expansion model based on the superposition of physical dimensions and the safety expansion radius. The robotic arm safety zone is constructed using a set of safety spheres with the rotation center of each joint as the sphere center and the safety expansion radius as the sphere diameter. The constructed cuboid expansion model of the chassis and the set model of the safety sphere of the robotic arm are spatially joined to generate the overall three-dimensional safety area of ​​the composite robot.

[0009] As a preferred technical solution, the heterogeneous safety module also includes a fault diagnosis module. This unit checks the consistency between the theoretical torque and the measured torque of the robotic arm joints and the theoretical speed and the measured speed of the chassis, and determines the abnormal state of the system by combining the threshold values.

[0010] As a preferred technical solution, the threshold refers to a threshold that is adaptively adjusted based on the standard deviation of the real-time calculation model error, as shown below: in, These represent the basic threshold values ​​for torque and velocity, respectively. , These represent the custom adjustment coefficients for torque and speed, respectively. , These represent the standard deviations of the torque and velocity model errors, respectively.

[0011] The present invention also provides an electronic device, comprising: The system includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the steps of the integrated controller for the composite robot as described above.

[0012] The present invention also provides a robot, including a robot body and the aforementioned electronic device, wherein the electronic device is communicatively connected to the robot body; the electronic device is disposed on the robot body, or the electronic device is separately disposed from the robot body.

[0013] The present invention also provides a storage medium storing at least one program that, when executed by a processor, implements the aforementioned integrated controller for a composite robot.

[0014] Compared with the prior art, the beneficial effects of this invention are: The integrated controller for composite robots provided by this invention integrates the perception, planning, and control logic of the robotic arm and chassis into the main control unit of the same hardware platform, and achieves task isolation and shared memory communication in the Hypervisor virtualization environment. This effectively solves the control fragmentation problem in distributed architecture and significantly improves the collaborative execution efficiency of multimodal tasks and the real-time response of the system. It introduces an intelligent safety strategy by integrating dynamic safety zone calculation and model-driven fault detection modules, enabling the system to achieve scenario-oriented proactive defense, breaking away from the traditional passive response mode and comprehensively improving the safety assurance capability and operational stability in complex industrial scenarios. Furthermore, it introduces an adaptive safety zone expansion and threshold adjustment strategy based on predictive uncertainty, which can effectively reduce the risk of safety strategy failure caused by external interference or model errors. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1This is a schematic diagram of the composition structure of the integrated controller for the composite robot of the present invention; Figure 2 This is a schematic diagram of the process for generating a three-dimensional safety area in the integrated controller for the composite robot of the present invention; Figure 3 This invention generates the overall three-dimensional safety area of ​​the composite robot in the integrated controller of the composite robot. Detailed Implementation

[0017] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0018] It should be noted that the terms "first" and "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0019] Figure 1 This is a schematic diagram of the composition structure of the integrated controller for the composite robot of the present invention, as shown below. Figure 1 As shown, this embodiment of the invention provides an integrated controller for a composite robot, including a main control unit integrated on the same hardware platform and an independent heterogeneous safety module; The main control unit runs on a processor with real-time scheduling capabilities and is used to integrate the perception, planning and control logic of the robotic arm and the chassis. The heterogeneous security module uses a processor with a different architecture than the main control unit to independently perform security monitoring and protection functions; The main control unit and the heterogeneous security module interact with each other through physically isolated communication links, and the security control logic is deployed separately from the conventional control logic.

[0020] In one specific implementation, the main control unit constructs a virtualized operating environment through a lightweight hypervisor to achieve isolated operation of robotic arm control tasks and chassis control tasks, with low-latency data synchronization between tasks via shared memory.

[0021] The main control unit is the core control hub of the system, running on an embedded processor with real-time scheduling capabilities. It integrates multiple functional sub-modules, including: a perception processing module for collecting and fusing data from various sensors such as LiDAR, cameras, and IMUs; a motion planning module for generating motion trajectories for the chassis and robotic arm based on current task and environmental perception information; a motion control module for issuing precise control commands to the actuators and providing real-time feedback loops; a communication module for standardized communication with the host computer, end effector, scheduling system, or other robots; and a safety logic module for implementing risk assessment at the main control level and task-level protection strategies.

[0022] This invention utilizes a physical isolation design between the main control unit and independent heterogeneous safety modules, along with processors of different architectures and physically isolated communication links, to achieve a complete separation between safety control logic and conventional control logic. Even if the main control unit fails, the heterogeneous safety modules can still independently perform safety monitoring and protection functions, thus strengthening the system's safety baseline. At the same time, the main control unit constructs a virtualized environment through a lightweight hypervisor, isolating the robotic arm and chassis control tasks while relying on shared memory to achieve low-latency data synchronization, balancing task independence and collaborative efficiency, and significantly optimizing the ability to handle complex tasks.

[0023] In one specific implementation, the heterogeneous safety module includes a dynamic safety area calculation module. This unit generates a set of future positions of the robot body and surrounding obstacles by predicting them, and dynamically generates a three-dimensional safety area based on position uncertainty parameters, thereby realizing the linkage obstacle avoidance between the robotic arm and the chassis.

[0024] As a preferred technical solution, Figure 2 This is a schematic diagram of the process for generating a three-dimensional safety area in the integrated controller for the composite robot of the present invention, as shown below. Figure 2 As shown, the dynamic safe area calculation module generates a three-dimensional safe area through the following steps: S1. Real-time acquisition of the current motion status information of the robot body and surrounding obstacles, including position, speed and acceleration; S2. Predict the trajectory of the robot and obstacles in the future time period, and simultaneously calculate the uncertainty of its position prediction; S3. Calculate the safety expansion radius based on the uncertainty covariance of the position prediction, and use it to expand the physical structure size of the robot in real time to generate a three-dimensional safety area that adapts to the motion state. S4. Continuously detect whether the predicted trajectory of the obstacle intersects with the three-dimensional safe area. If an intrusion occurs, trigger the robot's cooperative obstacle avoidance or emergency braking strategy.

[0025] In one specific implementation, the real-time acquisition of the current motion state information of the robot body and surrounding obstacles, including position, velocity, and acceleration, is achieved by collecting the real-time position, velocity, and acceleration of the robot and obstacles to construct a state vector X. k The result is represented as follows: ,in, Indicates location, Indicates speed, It represents acceleration.

[0026] In one specific implementation, the predicted trajectory of the robot and the obstacle in the future time period is achieved through a three-dimensional motion prediction model, the formula of which is expressed as follows: Where F is the state transition matrix, Δt is the sampling time interval, and Q is the process noise covariance matrix.

[0027] The state transition matrix F satisfies: .

[0028] In one specific implementation, the uncertainty of the location prediction is determined by the covariance matrix. The propagation formula is as follows: .

[0029] In one specific implementation, the safety expansion radius is calculated based on the uncertainty covariance of the location prediction, as shown below: Where, σ x ², σᵧ², σ_z² are P k+1 The position-related elements are λ, which is an adjustable coefficient.

[0030] In one specific implementation, Figure 3 To generate the overall three-dimensional safety area of ​​the composite robot in the integrated controller of the present invention, such as Figure 3 As shown, the real-time expansion of the robot's physical structure to generate a three-dimensional safety region that adaptively changes with the motion state includes: Safety zones are constructed for the chassis and the robotic arm respectively. The chassis safety zone is constructed using a cuboid expansion model based on the superposition of physical dimensions and the safety expansion radius. The robotic arm safety zone is constructed using a set of safety spheres with the rotation center of each joint as the sphere center and the safety expansion radius as the sphere diameter. The constructed cuboid expansion model of the chassis and the set model of the safety sphere of the robotic arm are spatially joined to generate the overall three-dimensional safety area of ​​the composite robot.

[0031] In one specific implementation, the length, width, and height of the expanded cuboid chassis model are calculated as follows: in, These are the physical dimensions of the chassis and the superstructure, respectively.

[0032] In one specific implementation, in the robotic arm safety sphere assembly model, it is assumed that the robotic arm has n joints, and the position of the i-th joint is... The radius of the safety sphere is calculated as follows: in, A preset fixed safety radius is used.

[0033] It should be further clarified that the robotic arm safety sphere assembly model represents the set of safety spheres corresponding to all joints. Furthermore, the real-time expansion of the robot's physical structure mentioned in this invention to generate a three-dimensional safety region that adaptively changes with the motion state is not limited to the cuboid expansion model of the chassis and the robotic arm safety sphere assembly model; other physical structure models of different shapes can also be used according to actual design.

[0034] The dynamic safety area calculation module in the heterogeneous safety module provided by this invention generates an adaptive three-dimensional safety area by acquiring motion state, predicted trajectory and uncertainty parameters in real time and combining them with the safety expansion radius. The chassis adopts a cuboid expansion model with physical size and expansion radius superimposed, and the robotic arm adopts a safety sphere set model with the joint center as the center of the sphere. The overall three-dimensional safety area is formed by spatial union operation, which can accurately detect the risk of obstacle intrusion and efficiently trigger linkage obstacle avoidance or emergency braking. Compared with the traditional static obstacle avoidance scheme, it is more suitable for dynamic and complex working environments and significantly reduces the risk of collision.

[0035] In one specific implementation, the heterogeneous safety module further includes a fault diagnosis module, which verifies the consistency between the theoretical torque and the measured torque of the robotic arm joints and the theoretical speed and the measured speed of the chassis, and determines the abnormal state of the system by combining the threshold values.

[0036] In one specific implementation, the theoretical torque of the robotic arm joint is calculated using a dynamic model, and is expressed as follows:

[0037] in, These represent the joint position, velocity, and acceleration vectors, respectively. Represents the joint inertia matrix. Represents the Coriolis force and centrifugal force matrices. This is the gravity compensation vector. This represents the coefficient of kinetic friction. This represents the Coulomb friction coefficient.

[0038] In one specific implementation, the steps for verifying the consistency between the theoretical torque and the measured torque of the robotic arm joint include: The error is obtained by comparing the theoretical torque of the robotic arm joint with the actual measured torque, as shown below: ; If the monitoring error exceeds the torque threshold, then... If this is detected, it indicates that there is an abnormality in the joint, which may include issues such as decreased actuator performance, sensor drift, or mechanical structure jamming.

[0039] In one specific implementation, the steps for verifying the consistency between the theoretical speed and the measured speed of the chassis include: In the process of predicting the motion trajectory of the robot and obstacles in the future time period, the velocity corresponding to the motion trajectory in the future time period is extracted. Compare it with the actual measured speed The comparison yields the following errors: ; If the monitoring error exceeds the speed threshold, then... If this is detected, it indicates that there is an abnormality in the joint, which may include problems such as drive system failure, wheel slippage, or abnormally increased load.

[0040] It should be noted that the extraction of the velocity corresponding to the motion trajectory within the future time period... That is, extraction Neutralize speed-related values.

[0041] In one specific implementation, the threshold refers to a threshold adaptively adjusted based on the standard deviation of the real-time calculation model error, as expressed below: in, These represent the basic threshold values ​​for torque and velocity, respectively. , These represent the custom adjustment coefficients for torque and speed, respectively. , These represent the standard deviations of the torque and velocity model errors, respectively.

[0042] In other words, the torque threshold and velocity threshold of this invention both adopt a threshold adaptive mechanism. When the standard deviation of the model error increases, the adjustment threshold is adaptively increased, which can reduce the false alarm rate caused by noise and environmental changes, and improve the stability and robustness of diagnosis.

[0043] It should be noted that the adaptive threshold can also be updated using an error threshold strategy based on a moving average or an exponentially weighted average to adapt to different noise levels and load conditions.

[0044] The fault diagnosis module of the heterogeneous safety module provided by this invention verifies the consistency between the theoretical and measured torques of the robotic arm joints and the theoretical and measured speeds of the chassis. Combined with threshold values, it accurately determines system anomalies, enabling early detection of potential faults or performance degradation, proactively mitigating the risk of escalating faults, and improving system robustness. Furthermore, the overall architecture offers advantages in functional expansion and scenario adaptability, flexibly adapting to different sensor and actuator types to meet the needs of diverse industrial environments.

[0045] The present invention also provides an electronic device, comprising: The electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the steps of the integrated controller for the composite robot as described above. The electronic device may also preferably include a communication interface for communicating and exchanging data with external devices.

[0046] It should be noted that the memory may include high-speed RAM, and may also include nonvolatile memory, such as at least one disk storage device.

[0047] In practical implementation, if the memory, processor, and communication interface are integrated on a single chip, they can communicate with each other through internal interfaces. If the memory, processor, and communication interface are implemented independently, they can be interconnected via a bus to communicate with each other.

[0048] The present invention also provides a robot, including a robot body and the aforementioned electronic device, wherein the electronic device is communicatively connected to the robot body; the electronic device is disposed on the robot body, or the electronic device is separately disposed from the robot body.

[0049] The present invention also provides a storage medium storing at least one program that, when executed by a processor, implements the aforementioned integrated controller for a composite robot.

[0050] It should be understood that the computer-readable storage medium is any data storage device capable of storing data or programs that can subsequently be read by a computer system. Examples of computer-readable storage media include read-only memory, random access memory, CD-ROM, HDD, DVD, magnetic tape, and optical data storage devices. Computer-readable storage media can also be distributed across network-coupled computer systems, enabling computer-readable code to be stored and executed in a distributed manner. The program code contained on the computer-readable storage medium can be transmitted using any suitable medium, including but not limited to: wireless, wired, optical fiber, radio frequency (RF), or any suitable combination thereof.

[0051] In some implementations, the computer-readable storage medium may be non-transitory.

[0052] Compared to existing technologies, the integrated controller for composite robots provided by this invention integrates the perception, planning, and control logic of the robotic arm and chassis into the main control unit of the same hardware platform, and achieves task isolation and shared memory communication in a hypervisor virtualization environment. This effectively solves the control fragmentation problem under distributed architecture, significantly improving the collaborative execution efficiency of multimodal tasks and the real-time response of the system. Furthermore, it introduces an intelligent safety strategy by integrating three-dimensional safety area calculation and model-driven fault detection modules, enabling the system to achieve proactive defense for specific scenarios, moving away from the traditional passive response mode and comprehensively improving safety assurance capabilities and operational stability in complex industrial scenarios. Finally, it introduces an adaptive safety area expansion and threshold adjustment strategy based on predictive uncertainty, which can effectively reduce the risk of safety strategy failure caused by external interference or model errors.

[0053] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0054] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. An integrated controller for a composite robot, characterized in that, This includes a main control unit integrated on the same hardware platform and independent heterogeneous security modules; The main control unit runs on a processor with real-time scheduling capabilities and is used to integrate the perception, planning and control logic of the robotic arm and the chassis. The heterogeneous security module uses a processor with a different architecture than the main control unit to independently perform security monitoring and protection functions; The main control unit and the heterogeneous security module interact with each other through physically isolated communication links, and the security control logic is deployed separately from the conventional control logic.

2. The integrated controller for the composite robot according to claim 1, characterized in that, The main control unit constructs a virtualized operating environment through a lightweight hypervisor, enabling isolated operation of robotic arm control tasks and chassis control tasks, with low-latency data synchronization between tasks via shared memory.

3. The integrated controller for the composite robot according to claim 2, characterized in that, The heterogeneous safety module includes a dynamic safety area calculation module. This unit generates a set of future positions of the robot body and surrounding obstacles by predicting them, and dynamically generates a three-dimensional safety area based on position uncertainty parameters, thereby realizing the linkage obstacle avoidance between the robotic arm and the chassis.

4. The integrated controller for the composite robot according to claim 3, characterized in that, The dynamic safe zone calculation module generates a three-dimensional safe zone through the following steps: Real-time acquisition of the current motion status information of the robot body and surrounding obstacles, including position, velocity and acceleration; Predict the trajectory of the robot and obstacles in the future and simultaneously calculate the uncertainty of its position prediction; Based on the uncertainty covariance of the position prediction, the safety expansion radius is calculated, and the physical structure dimensions of the robot are expanded in real time to generate a three-dimensional safety area that adapts to the motion state. The robot continuously detects whether the predicted trajectory of an obstacle intersects with the three-dimensional safe area. If an intrusion occurs, the robot's cooperative obstacle avoidance or emergency braking strategy is triggered.

5. The integrated controller for the composite robot according to claim 4, characterized in that, The real-time expansion of the robot's physical structure to generate a three-dimensional safety region that adaptively changes with its motion state includes: Safety zones are constructed for the chassis and the robotic arm respectively. The chassis safety zone is constructed using a cuboid expansion model based on the superposition of physical dimensions and the safety expansion radius. The robotic arm safety zone is constructed using a set of safety spheres with the rotation center of each joint as the sphere center and the safety expansion radius as the sphere diameter. The constructed cuboid expansion model of the chassis and the set model of the safety sphere of the robotic arm are spatially joined to generate the overall three-dimensional safety area of ​​the composite robot.

6. The integrated controller for the composite robot according to claim 5, characterized in that, The heterogeneous safety module also includes a fault diagnosis module, which verifies the consistency between the theoretical torque and the measured torque of the robotic arm joints and the theoretical speed and the measured speed of the chassis, and determines the abnormal state of the system by combining the threshold values.

7. The integrated controller for a composite robot according to claim 6, characterized in that, The threshold refers to a threshold that is adaptively adjusted based on the standard deviation of the real-time calculation model error, and is expressed as follows: in, These represent the basic threshold values ​​for torque and velocity, respectively. , These represent the custom adjustment coefficients for torque and speed, respectively. , These represent the standard deviations of the torque and velocity model errors, respectively.

8. An electronic device, characterized in that, include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the integrated controller for the composite robot as described in any one of claims 1-7.

9. A robot, characterized in that, It includes a robot body and the aforementioned electronic devices, wherein the electronic devices are communicatively connected to the robot body; the electronic devices are located on the robot body, or the electronic devices are separately located from the robot body.

10. A storage medium, characterized in that, It stores at least one program, characterized in that, when the program is executed by a processor, it implements the integrated controller for the composite robot as described in any one of claims 1-7.

Citation Information

Patent Citations

  • Multi-machine collaborative industrial robot intelligent scheduling system and application method

    CN119974019A

  • Double-mechanical-arm self-adaptive motor neural network optimization system

    CN120023827A

  • Industrial robot intelligent control system

    CN120347762A

  • System and method providing a priori temporal ensemble techniques for imitation learning-based robot task speedup

    KR102847985B1

  • Device control system and safety monitoring method for controlling a device

    WO2023052307A1