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arXiv 2303.02456cs.ROcs.SYeess.SY

具有时变工作空间约束的物理人机协作固定时间自适应神经控制

Fixed-time Adaptive Neural Control for Physical Human-Robot Collaboration with Time-Varying Workspace Constraints

Queen’s University Belfast(贝尔法斯特女王大学);University of Warwick(华威大学);National University of Singapore(新加坡国立大学)

Yuzhu Sun, Mien Van, Stephen McIlvanna, Nguyen Minh Nhat, Sean McLoone, Dariusz Ceglarek, Shuzhi Sam Ge

AI总结:

针对物理人机协作中的时变工作空间约束与接触柔顺需求,提出融合柔顺控制、TVIBLF和固定时间技术的自适应神经控制框架,并通过两连杆机械臂仿真验证其更优跟踪与收敛性能。

摘要:

物理人机协作(pHRC)需要同时具备柔顺性和安全保障,因为机器人要在共享工作空间中与人类动作相协调。本文提出了一种新颖的固定时间自适应神经控制方法,用于处理物理人机协作中出现的时变工作空间约束,同时保证在有意的力交互过程中具有柔顺性。所提方法结合了柔顺控制、时变积分障碍 Lyapunov 函数(TVIBLF)和固定时间技术的优点,不仅能够在与操作人员进行物理接触时实现柔顺,还能保证时变工作空间约束,并在对初始条件没有任何限制的情况下实现跟踪误差的快速收敛。此外,设计了一种神经自适应控制律,用于补偿机器人机械臂的未知动力学和扰动,使所提出的控制框架整体上固定时间收敛,并且能够在没有机器人动力学和扰动任何先验知识的情况下进行在线学习。所提方法最终在一个仿真的两连杆机器人机械臂上得到验证。仿真结果表明,与现有基于障碍 Lyapunov 函数的控制器相比,所提控制器在跟踪误差和收敛时间方面均更优,同时保证了柔顺性和安全性。

英文摘要:

Physical human-robot collaboration (pHRC) requires both compliance and safety guarantees since robots coordinate with human actions in a shared workspace. This paper presents a novel fixed-time adaptive neural control methodology for handling time-varying workspace constraints that occur in physical human-robot collaboration while also guaranteeing compliance during intended force interactions. The proposed methodology combines the benefits of compliance control, time-varying integral barrier Lyapunov function (TVIBLF) and fixed-time techniques, which not only achieve compliance during physical contact with human operators but also guarantee time-varying workspace constraints and fast tracking error convergence without any restriction on the initial conditions. Furthermore, a neural adaptive control law is designed to compensate for the unknown dynamics and disturbances of the robot manipulator such that the proposed control framework is overall fixed-time converged and capable of online learning without any prior knowledge of robot dynamics and disturbances. The proposed approach is finally validated on a simulated two-link robot manipulator. Simulation results show that the proposed controller is superior in the sense of both tracking error and convergence time compared with the existing barrier Lyapunov functions based controllers, while simultaneously guaranteeing compliance and safety.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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