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Risky planning: Path planning over costmaps with a probabilistically bounded speed-accuracy tradeoff

机译:有风险的计划:通过概率受限的速度精度折衷在成本图上进行路径计划

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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.
机译:本文是关于在不确定的地图上快速生成计划的。我们的方法结合了ALT(A *搜索,界标和三角形不等式)算法和风险启发法,以指导对概率成本图的搜索。我们以先前的工作为基础,该工作从航空影像生成概率成本图,并使用这些成本图通过ALT技术预先计算启发式搜索,例如A *和D *。结果启发式法是概率分布。我们可以通过表征准备在提高最佳搜索路径长度的同时提高搜索效率的风险来加速和直接搜索。结果表明,ALT可以很好地逼近启发式算法的真实分布,并且与常规启发式搜索方法相比,其效率提高了70%以上。

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