ARA*+: Improved Path Planning Algorithm Based on ARA*

Bo Li, Jian-wei Gong, Yan Jiang, Hany Nasry, Guang-ming Xiong
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引用次数: 10

Abstract

A* path planning algorithm cannot always guarantee the continuity of a robot's movements when the allocated time is limited, however Anytime Repairing A*(ARA*) can get a sub-optimal solution quickly, and then work on improving the solution until the allocated time expires. This paper proposes a variation of ARA* algorithm (ARA*+) which executes multiple Weighted A* to search the solution. During the first search of ARA*+, Weighted A* with a bigger inflation factor is applied and no state is expanded more than once, in this way, the time needed for finding a sub-optimal solution can be remarkably shortened. Then, Weighted A* will be executed again for better path, by decreasing the inflation factor and reusing the previous planning efforts. Here, with the same inflation factor the expanded states can be used again, and this is different from ARA*, which forbids the expanded states to be expanded again. If the allocated time does not expire, this process will not stop until the optimal solution is found, or the current sub-optimal solution will be regarded as the output. According to our robot path planning experiments, in most cases the number of expanded states in ARA*+ was smaller than that in ARA*, as a result, the time spent to get the optimal solution will be shorter.
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ARA*+:基于ARA*的改进路径规划算法
A*路径规划算法在分配时间有限的情况下,不能保证机器人运动的连续性,而随时修复A*(ARA*)算法可以快速得到次优解,然后不断改进解,直到分配时间到期。本文提出了一种ARA*算法的变体(ARA*+),它执行多个加权a *来搜索解。在ARA*+的第一次搜索中,使用膨胀因子较大的加权A*,并且状态的扩展不超过一次,这样可以显著缩短寻找次优解所需的时间。然后,通过减少膨胀因子和重用之前的规划工作,再次执行加权A*以获得更好的路径。这里,在相同的膨胀因子下,可以再次使用膨胀状态,这与ARA*不同,ARA*禁止膨胀状态再次膨胀。如果分配的时间没有过期,则该进程不会停止,直到找到最优解,或者将当前次优解视为输出。根据我们的机器人路径规划实验,在大多数情况下,ARA*+中的展开状态数比ARA*中的要少,因此得到最优解的时间会更短。
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