Anytime, Dynamic Planning in High-dimensional Search Spaces

— We present a sampling-based path planning and replanning algorithm that produces anytime solutions. Our algorithm tunes the quality of its result based on available search time by generating a series of solutions, each guaranteed to be better than the previous ones by a user-defined improvement bound. When updated information regarding the underlying search space is received, the algorithm efficiently repairs its previous solution. The result is an approach that provides lowcost solutions to high-dimensional search problems involving partially-known or dynamic environments. We discuss theoretical properties of the algorithm, provide experimental results on a simulated multirobot planning scenario, and present an implementation on a team of outdoor mobile robots.

• Type: Conference
• Year: 2007
• Where: ICRA
• Authors: Dave Ferguson, Anthony Stentz
• Keywords: Algorithm, Available Search Time, ICRA 2007, Robotics, Sampling-based Path Planning