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Improvements of force tracking performances for a minimal surgery training system using haptic and robot devices

机译:使用触觉和机器人设备的最小型手术培训系统的力跟踪性能的改进

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This paper presents the closed loop teleoperation of a minimal surgery training system using haptic and robot devices. The force tracking performances of system can be improved by using dynamic compensation and fuzzy control. In this system, the master is the 6-DOF haptic device and the slave is the 6-DOF serial robot. The master haptic device provides the trajectories for the slave serial robot throught the operation of user's hand on the steering handle while the slave robot sends feedback forces on its end effector to the master controller in order to generate forces/moments on the steering handle of haptic master. In this manner the user's hand will feel the forces/moments as the same those of the robot end effector. Because dynamics of the master haptic device affects directly to the performances of control actions, it should be calculated to compensate in the control algorithms. Inverse dynamics combined with fuzzy control is used to compensate for actual dynamics of the haptic master in the real closed loop teleoperation system. Experiment results indicate that the dynamic compensation and fuzzy control can improve the control performances effectively.
机译:本文介绍了使用触觉和机器人设备的最小手术培训系统的闭环远程操作。动态补偿和模糊控制可以提高系统的力跟踪性能。在此系统中,主设备是6自由度触觉设备,从设备是6自由度串行机器人。主触觉设备通过用户在操纵手柄上的手的操作为从属串行机器人提供轨迹,而从属机器人将其末端执行器上的反馈力发送给主控制器,以便在触觉操纵柄上产生力/力矩掌握。以这种方式,用户的手将感觉到与机器人末端执行器相同的力/力矩。由于主触觉设备的动力学直接影响控制动作的性能,因此应在控制算法中对其进行计算以进行补偿。逆动力学与模糊控制相结合,用于补偿实际闭环遥操作系统中触觉主机的实际动力学。实验结果表明,动态补偿和模糊控制可以有效地提高控制性能。

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