The paper presents a comprehensive performance evaluation of some heuristic search algorithms in the context of autonomous systems and robotics. The objective of the study is to evaluate and compare the performance of different search algorithms in different problem settings on the pathfinding domain. Experiments give us insight into the behavior of the evaluated heuristic search algorithms, over the variation of different parameters: domain size, obstacle density, and distance between the start and the goal states. Results are then used to design a selection algorithm that, on the basis of problem characteristics, suggests the best search algorithm to use.

翻译：本文对自主系统与机器人领域中若干启发式搜索算法进行了综合性能评估。研究目的在于针对寻路任务的不同问题设定，评估并比较多种搜索算法的性能表现。通过实验，我们深入分析了所评估的启发式搜索算法在领域规模、障碍物密度及起始与目标状态间距离等参数变化下的行为特征。基于实验结果，我们设计了一种选择算法，该算法能够根据问题特性自动推荐最优搜索方案。