COMPARISON OF EXPLORATION STRATEGIES FOR MULTI-ROBOT SEARCH

Abstract

Searching for a stationary object in an unknown environment can be formulated as an iterative procedure consisting of map updating, selection of a next goal and navigation to this goal. It finishes when the object of interest is found. This formulation and a general search structure is similar to the related exploration problem. The only difference is in goal-selection, as search and exploration objectives are not the same. Although search is a key task in many search and rescue scenarios, the robotics community has paid little attention to the problem. There is no goal-selection strategy that has been designed specifically for search. In this paper, we study four state-of-the-art strategies for multi-robot exploration, and we evaluate their performance in various environments with respect to the expected time needed to find an object, i.e. to achieve the objective of the search.