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.
Published Version
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