面向等曝光走廊的曝光感知路径规划
Exposure Conscious Path Planning for Equal Exposure Corridors
AI总结：
本研究针对导航中最小化环境视线曝光以降低探测风险的问题，指出该问题具非马尔可夫性无法用传统路径规划高效求最优解，分析了A*算法的最优性差距与近似启发式的权衡，并提出可多项式时间确定低曝光路径的等曝光走廊概念。
摘要：
尽管最大化环境中特定区域或智能体的视线覆盖度是一个已被充分研究的路径规划目标，但与之相反的、在导航过程中最小化对整个环境的曝光的问题，在降低探测风险的场景中尤为值得关注。本研究表明，最小化对环境的视线曝光具有非马尔可夫性，无法通过传统路径规划方法高效求得最优解。本文探究了图搜索算法A*的最优性差距，以及多种近似启发式算法在最优性与计算时间之间的权衡。最后，本文提出了等曝光走廊的概念，该概念支持在多项式时间内确定所有不会增加曝光量的路径。
英文摘要：
While maximizing line-of-sight coverage of specific regions or agents in the environment is a well-explored path planning objective, the converse problem of minimizing exposure to the entire environment during navigation is especially interesting in the context of minimizing detection risk. This work demonstrates that minimizing line-of-sight exposure to the environment is non-Markovian, which cannot be efficiently solved optimally with traditional path planning. The optimality gap of the graph-search algorithm A* and the trade-offs in optimality vs. computation time of several approximating heuristics is explored. Finally, the concept of equal-exposure corridors, which afford polynomial time determination of all paths that do not increase exposure, is presented.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
