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An adaptive discretized RNN algorithm for posture collaboration motion control of constrained dual-arm robots
Yichen Zhang1, Yu Han1, Binbin Qiu1
1School of Intelligent Systems Engineering, Sun Yat-sen University, Shenzhen, China.
Frontiers in Neurorobotics
|June 6, 2024
Summary
This study introduces a dual-arm posture collaboration motion control (DAPCMC) scheme for robots, utilizing an adaptive Taylor-type recurrent neural network (ATT-DRNN) for precise and fast control in complex 3D tasks.
Area of Science:
- Robotics
- Control Systems Engineering
- Artificial Intelligence
Background:
- Repetitive motion control in robotics is well-studied.
- Limited research exists on posture collaboration motion control for constrained dual-arm robots in 3D environments.
- Complex tasks require advanced control strategies for multi-arm robotic systems.
Purpose of the Study:
- To develop a novel dual-arm posture collaboration motion control (DAPCMC) scheme for constrained robots in 3D space.
- To address the challenges of balancing calculation accuracy and convergence speed in robotic motion control.
- To propose an effective algorithm for solving time-variant equation system (TVES) problems in robotics.
Main Methods:
- Established a minimum displacement repetitive motion control scheme for individual robotic arms.
- Integrated a new joint-limit conversion strategy into the DAPCMC scheme.
- Devised a novel adaptive Taylor-type discretized recurrent neural network (ATT-DRNN) algorithm to solve the TVES problem.
Main Results:
- The ATT-DRNN algorithm demonstrates a superior balance between calculation accuracy and fast convergence speed.
- Theoretical analysis confirmed the algorithm's dependability in precision and convergence rate.
- Numerical simulations and control cases validated the effectiveness of the DAPCMC scheme and the ATT-DRNN algorithm.
Conclusions:
- The proposed DAPCMC scheme effectively enables posture collaboration motion control for dual-arm robots.
- The ATT-DRNN algorithm provides a robust and efficient solution for complex robotic control problems.
- This research advances the capabilities of dual-arm robots in performing intricate tasks in 3D environments.
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