A motion planning based approach for inverse kinematics ofredundant robots: the kinematic roadmap

摘要

We propose a new approach to solving the point-to-point inversekinematics problem for highly redundant manipulators. It is inspired byrecent motion planning research and explicitly takes into accountconstraints due to joint limits and self-collisions. Central to ourapproach is the novel notion of kinematic roadmap for a manipulator. Thekinematic roadmap captures the connectivity of the configuration spaceof a manipulator in a finite graph like structure. The standardformulation of inverse kinematics problem is then solved using thisroadmap. Our current implementation, based on Ariadne's clew algorithm,is composed of two sub-algorithms: EXPLORE, a simple algorithm thatbuilds the kinematic roadmap by placing landmarks in the configurationspace; and SEARCH, a local planner that uses this roadmap to reach thedesired end-effector configuration. Our implementation of SEARCH is anextremely efficient closed form solution, albeit local, to inversekinematics that exploits the serial kinematic structure of serialmanipulator arms. Initial experiments with a 7-DOF manipulator have beenextremely successful