Improving backdrivability in preoperative manual manipulability of minimally invasive surgery robot
ISSN: 0143-991X
Article publication date: 13 December 2017
Issue publication date: 2 January 2018
Abstract
Purpose
The purpose of this paper is to propose a control algorithm to improve the backdrivability performance of minimally invasive surgical robotic arms, so that precise manual manipulations of robotic arms can be performed in the preoperative operation.
Design/methodology/approach
First, the flexible-joint dynamic model of the 3-degree of freedom remote center motion (RCM) mechanisms of minimally invasive surgery (MIS) robot is derived and its dynamic parameters and friction parameters are identified. Next, the angular velocities and angular accelerations of joints are estimated in real time by the designed Kalman filter. Finally, a control algorithm based on Kalman filter is proposed to enhance the backdrivability of RCM mechanisms by compensating for the internally generated gravitational, frictional and inertial resistances experienced during the positioning and orientating.
Findings
The parameter identification for RCM mechanisms can be experimentally evaluated from comparison between the measured torques and the reconstructed torques. The accuracy and convergence of the real-time estimation of angular velocity and acceleration of the joint by the designed Kalman filter can be verified from corresponding simulation experiments. Manual adjustment experiments and animal experiments validate the effectiveness of the proposed backdrivability control algorithm.
Research limitations/implications
The backdrivability control algorithm presented in this paper is a universal method to enhance the manual operation performance of robots, which can be used not only in the medical robot preoperative manual manipulation but also in robot haptic interaction, industrial robot direct teaching and active rehabilitation training of rehabilitation robot and so on.
Originality/value
Compared with other backdrivability design methods, the proposed algorithm achieves good backdrivability for RCM mechanisms without using force sensors and accelerometers. In addition, this paper presents a new static friction compensation approach for a joint moving with very low velocity.
Keywords
Acknowledgements
This work was supported by the National High Technology Research and Development Program of China (“863 Program”) (Grant No. 2012AA041601), the National Natural Science Foundation of China (Grant No.61305139), Self-Planned Task (No. SKLRS201406B) of State Key Laboratory of Robotics and System (HIT), the Fundamental Research Funds for the Central Universities (Grant No. HIT. NSRIF. 2013052).
Citation
Zou, S., Pan, B., Fu, Y. and Guo, S. (2018), "Improving backdrivability in preoperative manual manipulability of minimally invasive surgery robot", Industrial Robot, Vol. 45 No. 1, pp. 127-140. https://doi.org/10.1108/IR-02-2017-0031
Publisher
:Emerald Publishing Limited
Copyright © 2018, Emerald Publishing Limited