Path planning for nonholonomic mobile manipulators grasping based on multi-objective constraint

Abstract

This paper presents a path planning algorithm for nonholonomic mobile manipulators multi-objective grasping that computes the mobile platform trajectory by maximizing the manipulability measures. The objective of the method is to find the best platform pose when the robot end-effector grasps object whose pose has been obtained by the visual system already. Firstly, we analyzed the distribution of operating performance of the manipulator inside its working space by manipulability measure. Then, we calculated the best platform pose by maximizing the manipulability measures, meanwhile took multi-objective and nonholonomic constraints into account. Finally, we controlled the mobile manipulators to approach the object by posture stabilization algorithm and picked it up by manipulator according to the result of inverse kinematics. The proposed method has been validated practicability and effectiveness by simulation examples and grasping experiment.