多侦察机器人路径间隙的信息价值驱动方法

M. Likhachev, A. Stentz
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引用次数: 3

摘要

在路径清除问题中,机器人需要在不被敌人发现的情况下尽可能快地到达目标。机器人不知道敌人的精确位置,但有一个他们可能的位置列表。这些位置可以被感知,如果没有敌人存在,机器人可以穿过它们,或者必须绕道而行。我们之前已经开发了一种方法来解决路径清除问题,当机器人自己必须感知可能的敌人位置时。本文研究了当机器人可以使用多个侦察机器人来感知可能的敌人位置时的路径间隙问题。这就成为一个不确定问题下的高维规划问题。我们提出了一种有效且可扩展的方法。虽然该方法需要集中规划,但它可以扩展到非常大的环境和大量的侦察员,并允许侦察员是异构的。实验结果表明,当多个侦察机器人可用时,使用我们的方法是有益的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Information value-driven approach to path clearance with multiple scout robots
In the path clearance problem the robot needs to reach its goal as quickly as possible without being detected by enemies. The robot does not know the precise locations of enemies, but has a list of their possible locations. These locations can be sensed, and the robot can go through them if no enemy is present or has to take a detour otherwise. We have previously developed an approach to the path clearance problem when the robot itself had to sense possible enemy locations. In this paper we investigate the problem of path clearance when the robot can use multiple scout robots to sense the possible enemy locations. This becomes a high-dimensional planning under uncertainty problem. We propose an efficient and scalable approach to it. While the approach requires centralized planning, it can scale to very large environments and to a large number of scouts and allows the scouts to be heterogenous. The experimental results show the benefits of using our approach when multiple scout robots are available.
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