On integrating manipulability index into inverse kinematics solver
作者: Kévin Dufour, Wael Suleiman
摘要
This paper presents a method to maximize the manipulability index of a redundant industrial manipulator while solving the Inverse Kinematics (IK) problem as an optimization problem. Even though the IK problem is a widely studied topic, the integration of the manipulability index into IK has rarely been taken into account. As the relation between this index and the joint variables of the robot is not straightforward, we have tested different formulations using approximated derivatives. Obstacle avoidance has also been considered and the effect of modifying the Cartesian trajectory during the execution of a task has been thoroughly analyzed. Different scenarios have been conducted in simulation and have proven that our modified inverse kinematics solver is efficient to maximize the manipulability index, even with the additional constraint of obstacle avoidance. Moreover, the relaxation of the trajectory constraints leads to a greater manipulability while ensuring the motion smoothness and satisfying the robot physical limitations.