Optimal Motion Planning for Multiple Robots Having Independent Goals - Robotics and Automation, IEEE Transactions on

This work makes two contributions to geometric motion planning for multiple robots: 1) motion plans are computed that simultaneously optimize an independent performance measure for each robot; 2) a general spectrum is defined between decoupled and centralized planning, in which we introduce coordination along independent roadmaps. By considering independent performance measures, we introduce a form of optimality that is consistent with concepts from multiobjective optimization and game theory literature. Previous multiple-robot motion planning approaches that consider optimality combine individual performance measures into a scalar criterion. As a result, these methods can fail to find many potentially useful motion plans. We present implemented, multiplerobot motion planning algorithms that are derived from the principle of optimality, for three problem classes along the spectrum between centralized and decoupled planning: 1) coordination along fixed, independent paths; 2) coordination along independent roadmaps; 3) general, unconstrained motion planning. Computed examples are presented for all three problem classes that illustrate the concepts and algorithms.