Information Value-Driven Approach to Path Clearance with Multiple Scout Robots

Maxim Likhachev* and Anthony Stentz**

*University of Pennsylvania, **Carnegie Mellon University



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.


Keywords: path clearance, planning, planning under uncertainty, multi-robot coordination, planning with adversaries