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Biomimetic joint/task space hybrid adaptive control for bimanual robotic manipulation

机译:用于双手机器人操纵的仿生关节/任务空间混合自适应控制

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In this paper, we study the adaptive control of a bimanual manipulator moving a dynamic object through a trajectory. Impedance and force are adapted online using a novel biomimetic algorithm that minimises both tracking error and control effort, as observed in humans. On top of our previous work of impedance and force adaptation, a new task space/joint-space hybrid control scheme is developed. The task space controller adapts end-point impedance, to compensate for interactive dynamics, and the joint-space controller adapts the impedance to improve robustness against external disturbances. Extensive simulations demonstrate the efficiency of the developed adaptive motion controller. The results show that the proposed hybrid controller can perform well under large disturbance conditions while minimising control effort and tracking error.
机译:在本文中,我们研究了通过轨迹移动动态对象的双向机械手的自适应控制。使用在人类中观察到的新型仿生算法,可在线最小化跟踪误差和控制力,从而调整阻抗和力。在我们之前的阻抗和力适应工作的基础上,开发了一种新的任务空间/关节空间混合控制方案。任务空间控制器调整端点阻抗,以补偿交互式动态,关节空间控制器调整阻抗,以提高抵抗外部干扰的鲁棒性。大量的仿真证明了开发的自适应运动控制器的效率。结果表明,所提出的混合控制器在大扰动条件下性能良好,同时最大程度地减少了控制工作量和跟踪误差。

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