Planning Paths Through A Spatial Hierarchy: Eliminating Stair-Stepping Effects

Many of the current approaches toward the creation of an intelligent robotic system involve the creation and maintenance of an explicit world model. One such world model decomposes space into a hierarchical grid, representing spatial features of interest in high detail and those of lesser interest in lower detail. These models provide an effective interface for sensory information as well as an efficient mechanism for performing spatial inferences. Although hierarchical decompositions provide efficient representations of space, paths generated by planning systems operating within such representations tend to suffer from stair-stepping effects. Stair-stepping effects are a result of the loss of spatial continuity resulting from the decomposition of space into a grid. This paper presents a path planning algorithm which eliminates stair-stepping effects induced by the grid-based spatial representation. The algorithm exploits a hierarchical spatial model to efficiently plan paths for a mobile robot operating in dynamic domains. The spatial model and path planning algorithm map to a parallel machine, allowing the system to effectively operate incrementally, thereby accounting for unexpected events in the operating space.