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Risky Planning: Path Planning over Costmaps with a Probabilistically Bounded Speed-Accuracy Tradeoff

机译:风险规划:具有概率界限速度折衷的花费花费花费的路径规划

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This paper is about generating plans over uncer-tain 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.
机译:本文是关于快速地在Uncer-Tain地图上产生计划。我们的方法结合了ALT(A〜*搜索,地标和三角形不等式)算法和风险启发式,以指导搜索概率成本图。我们建立在以前的工作中,从空中图像产生概率的成本映射,并使用这些成本图以使用ALT技术的搜索搜索的启发式方法。由此产生的启发式是概率分布。我们可以通过表征风险来加速和直接搜索,我们准备在牺牲最佳路径长度的同时获得搜索效率。结果表明,Alt提供了良好的近似对启发式的真实分布,并且在正常启发式搜索方法上显示出超过70%的效率增加。

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