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A decentralized optimal control strategy that incorporates cooperative game theory is devised for robotic in the context of physical human-robot interaction (pHRI). The primary aim of achieving optimal control in the context of pHRI shifts toward the approximation of Pareto equilibrium by employing a cooperative game framework in which both the human and the reconfigurable robot manipulator (RRM) serve as participants with distinct roles and optimization goals during their interactions. Utilizing the ADP algorithm, a decentralized strategy for approximate optimal control incorporating pHRI has been established. The position error has been confirmed to exhibit UUB. Results from the experiment have been showcased, demonstrating clear advantages.

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Cooperative Game-Based Decentralized Approximate Optimal Control for Reconfigurable Robot Manipulators with Physical Human-Robot Interaction

  • 会议论文

  • 发表日期：

    2025年

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  • Tianjiao An,
  • Haoyu Yan,
  • Bing Ma,
  • Hucheng Jiang,
  • Bo Dong

摘要

A decentralized optimal control strategy that incorporates cooperative game theory is devised for robotic in the context of physical human-robot interaction (pHRI). The primary aim of achieving optimal control in the context of pHRI shifts toward the approximation of Pareto equilibrium by employing a cooperative game framework in which both the human and the reconfigurable robot manipulator (RRM) serve as participants with distinct roles and optimization goals during their interactions. Utilizing the ADP algorithm, a decentralized strategy for approximate optimal control incorporating pHRI has been established. The position error has been confirmed to exhibit UUB. Results from the experiment have been showcased, demonstrating clear advantages.