Variable impedance control based on the surgeon’s motion intention for robot-assisted minimally invasive surgery

The paper focuses on incorporating the surgeon’s motion intention into impedance control, which is one of the most commonly used control schemes in master manipulation, to reduce the user’s motion efforts. To achieve this, the non-autoregressive spatio-temporal transformer network is applied to predict the surgeon’s motion trajectory, which is described by the control points of B-spline. The study investigates the effects of input data length, data feature, and feedforward data on trajectory prediction. Furthermore, a Cartesian variable impedance control strategy without force sensor is implemented by adjusting the damping parameters according to the future external force. The experiment shows a promising result, where the interactive force under this control strategy is lower than the one with the current external force, and the precise operation still performs well.