2020/03/04 by Diane Uwacu, Uwacu, Diane, Regina Rex +7
Computer Science · Engineering · #Advanced Image and Video Retrieval Techniques #Biomolecules (q-bio.BM) #FOS: Biological sciences #FOS: Computer and information sciences #Robotic Path Planning Algorithms #Robotics (cs.RO) #Robotics and Sensor-Based Localization
paper · pdf · doi:10.48550/arxiv.2003.02176
openalex publication_date 2020/03/04 · openalex created_date 2020/03/13 · openalex updated_date 2026/07/28
Motion planning algorithms often leverage topological information about the environment to improve planner performance. However, these methods often focus only on the environment's connectivity while ignoring other properties such as obstacle clearance, terrain conditions, and resource accessibility. We present a method that augments a skeleton representing the workspace topology with such information to guide a sampling-based motion planner to rapidly discover regions most relevant to the problem at hand. Our approach decouples guidance and planning, making it possible for basic planning algorithms to find desired paths earlier in the planning process. We demonstrate the efficacy of our approach in both robotics problems and applications in drug design. Our method is able to produce desirable paths quickly with no change to the underlying planner.