Robot motion planning: A game-theoretic foundation

This paper proposes a dynamic game-theoretic framework that is used as an analytical tool and unifying perspective for a wide class of problems in motion planning. This approach is inspired by the foundation laid by configuration-space concepts for basic path planning. In the same manner that configuration-space concepts led to substantial progress in path planning, game-theoretic concepts provide a more general foundation which can, incorporate ally of the essential features of path planning, sensing uncertainty, decision theory, bounded-uncertainty analysis, stochastic optimal central, and traditional multiplayer games. By following this perspective, new modeling, analysis, algorithms, and computational results have been obtained for a variety of motion planning problems including those involving uncertainty in sensing and control, environment uncertainties, and the coordination of multiple robots.