Anytime path planning in graduated state space
Haojie Zhang, Guangming Xiong, Bo Su, Jianwei Gong, Yan Jiang, Huiyan Chen, Wei Lan · 2013
Complex robotic systems often have to operate in large environments. At the same time, their dynamic is complex enough that path planning algorithms need to reason about the kinodynamic constraints of these systems. On the other hand, such robotic systems are typically expected to operate with speed that is commensurate with that of humans. This poses stringent limitation on available planning time. These will result in a contradiction between planning efficiency and the dimensions of the state space determined by the kinodynamic constraints. In this paper we present an anytime path planning algorithm to solving this problem. First, a graduated state space which consists of state lattices and grids is constructed for planning. Then, ARA* algorithm is utilized to search the graduated state space to find a path that satisfies the kinodynamic constraints and available runtime of planning.