Obstacle avoidance using hierarchical dynamic programming

Studies the problem of finding the optimal path or trajectory of a robot or other unmanned device through an obstacle field for a given start and goal position. In the most general problem, the obstacle field would be modeled by a finite array of time dependent analog valued pixels. Moreover since the field of vision of the unmanned device is limited, the authors could not assume perfect knowledge of the full obstacle field at any given time. The author discuss approximate optimal paths constructed using hierarchical methods. The hierarchical methods entail constructing a coarse resolution version of the original obstacle array and then using multipass dynamic programming to find an optimal coarse path