OVERVIEW OF DAMPED LEAST-SQUARES METHODS FOR INVERSE KINEMATICS OF ROBOT MANIPULATORS

In this paper, we present a tutorial report of the literature on the d amped-least squares method which has been used for computing velocity inverse kinematics of robotic manipulators. This is a local optimizati on method that can prevent infeasible joint velocities near singular c onfigurations by using a damping factor to control the norm of the joi nt velocity vector. However, the exactness of the inverse kinematic so lution has to be sacrificed in order to achieve feasibility. The dampi ng factor is an important parameter in this technique since it determi nes the trade-off between the accuracy and feasibility of the inverse kinematic solution. Various methods that have been proposed to compute an appropriate damping factor are described. Redundant manipulators, possessing extra degrees of freedom, afford more choice of inverse kin ematic solutions than do non-redundant ones. The damped least-squares method has been used in conjunction with redundancy resolution schemes to compute feasible joint velocities for redundant arms while perform ing an additional subtask. We outline the different techniques that ha ve been proposed to achieve this objective. In addition, we introduce an iterative method to compute the optimal damping factor for one of t he redundancy resolution techniques.