Varying paths and motion profiles in multiple robot motion planning

We show how using anytime algorithms for solving the multiple robots motion planning problem allows to evaluate the opportunity of looking for alternative solution paths by generating small variations of robot motions in space and in time. By using the concept of plan robustness, we generate several alternative paths that are evaluated through various Performance Indices and Impact Factors, that allow to know how much a variation affects a given plan. Finally, we outline some recent experiments.