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Human-robot interaction control of a haptic master manipulator used in laparoscopic minimally invasive surgical robot system
Mechanism and Machine Theory ( IF 5.2 ) Pub Date : 2021-02-01 , DOI: 10.1016/j.mechmachtheory.2020.104132
Zhijiang Du , Yunlei Liang , Zhiyuan Yan , Lining Sun , Wei Chen

Abstract As an interface for physical human-robot interaction (pHRI), the master manipulator of robot-assisted surgery system is critical to the success rate of surgical procedures. In this paper, a pHRI control scheme of the haptic master manipulator used in laparoscopic surgical robots is presented for enhancing the precision and comfort of operations. Firstly, the inverse dynamic equations of the master manipulator are derived and a modified friction model is proposed to improve the accuracy of friction torque calculation. Then a torque observer based on generalized momentum is designed. The proposed observer can precisely track the joint driving torque needed by the motion state and comply with the operator's intentions. Thirdly, the compensator based on time-delay neural network (TDNN) is proposed to improve the performance of pHRI. Finally, the pHRI control strategy which can adjust the degree of operation compliance actively is introduced. The results of theoretical analysis and comparative experiments indicate that the proposed strategy can substantially reduce the force and torque applied to surgeons by the master manipulator during the operation.

中文翻译:

用于腹腔镜微创手术机器人系统的触觉主机械手的人机交互控制

摘要 作为物理人机交互(pHRI)的接口,机器人辅助手术系统的主机械手对手术的成功率至关重要。在本文中,提出了一种用于腹腔镜手术机器人的触觉主机械手的 pHRI 控制方案,以提高操作的精度和舒适度。首先推导了主机械手的逆动力学方程,并提出了改进的摩擦模型,以提高摩擦力矩计算的准确性。然后设计了基于广义动量的转矩观测器。所提出的观测器可以精确跟踪运动状态所需的关节驱动扭矩,并符合操作者的意图。第三,提出了基于时延神经网络(TDNN)的补偿器来提高pHRI的性能。最后,介绍了可主动调节操作合规程度的pHRI控制策略。理论分析和对比实验结果表明,所提出的策略可以显着降低主机械手在手术过程中施加给外科医生的力和扭矩。
更新日期:2021-02-01
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