Probabilistic motion planning for redundant robots along given end-effector paths

We consider the problem of planning collision-free motions for a redundant robot whose end-effector must travel along a given path. Although collision avoidance is one of the main reasons for introducing kinematic redundancy in manipulators, the planning methods so far proposed for this particular problem are neither efficient nor complete. In this paper, we introduce some algorithms that may be considered as an extension of probabilistic planning techniques to the problem at hand. All the algorithms are based on the same simple mechanism for generating random samples of the configuration space that are compatible with the end-effector path constraint. Experimental results illustrate the performance of the planners.