Joint Path and Push Planning Among Movable Obstacles
This addresses path planning in cluttered environments with movable obstacles, offering incremental improvements over existing methods.
The paper tackles the Navigation Among Movable Obstacles problem by proposing a joint path and push planning algorithm, which finds solutions in up to 49% clutter compared to 37% for a straight-line push planner and 18% for RRT without pushing.
This paper explores the Navigation Among Movable Obstacles (NAMO) problem and proposes joint path and push planning: which path to take and in what direction the obstacles should be pushed at, given a start and goal position. We present a planning algorithm for selecting a path and the obstacles to be pushed, where a Rapidly-exploring Random Tree (RRT)-based heuristic is employed to calculate a minimal collision path. When it is necessary to apply a pushing force to slide an obstacle out of the way, the planners leverage means-end analysis through a dynamic physics simulation to determine the sequence of linear pushes to clear the necessary space. Simulation experiments show that our approach finds solutions in higher clutter percentages (up to 49%) compared to the straight-line push planner (37%) and RRT without pushing (18%).