Risky Planning: Path Planning over Costmaps with a Probabilistically Bounded Speed-Accuracy Tradeoff
This paper is about generating plans over uncertain maps quickly. Our approach combines the ALT (A* search, landmarks and the triangle inequality) algorithm and risk heuristics to guide search over probabilistic cost maps.We build on previous work which generates probabilistic cost maps from aerial imagery and use these cost maps to precompute heuristics for searches such as A* and D* using the ALT technique. The resulting heuristics are probability distributions. We can speed up and direct search by characterising the risk we are prepared to take in gaining search efficiency while sacrificing optimal path length. Results are shown which demonstrate that ALT provides a good approximation to the true distribution of the heuristic, and which show efficiency increases in excess of 70％ over normal heuristic search methods.
Liz Murphy Paul Newman
School of Engineering Systems,Queensland University of Technology Oxford University Mobile Robotics Group
国际会议
2011 IEEE International Conference on Robotics and Automation(2011年IEEE世界机器人与自动化大会 ICRA 2011)
上海
英文
3727-3732
2011-05-09（万方平台首次上网日期，不代表论文的发表时间）