A novel approach for flexible manipulator conducting screwing task based on robot–environment contact classification

Abstract

Bolt screwing assembly task is a crucial part for robot fine manipulation. For widely applied flexible joints robot with six-dimensional force/torque sensor, data collected could not be seen as the contact force since it consists of internal force caused by deformation of the manipulator joints. Force analysis and geometric analysis could not be applied to judge the relative pose between robot end-effector and the environment. To this end, logistic regression method was used to classify the contact state by force signals. Besides, the criterion that bolt has entered the thread hole is also significant, while a boundary condition was proposed to solve this problem. A bolt screwing experiment was conducted to evaluate the proposed strategy, and the results demonstrate the effectiveness of the contact state classification and the boundary condition for judging the bolt entering the thread hole.