Rapid multi-robot exploration with topometric maps

Abstract

Multi-robot map building has advanced to the point where high quality occupancy grid data may be collected by multiple robots collaborating with only intermittent connectivity. However, the tasking of these agents to most efficiently build the map is a problem that has seen less attention. Unfamiliar, highly cluttered environments can con found exploration strategies that rely solely on occupancy grid frontier identification or even semantic classification methods keyed on geometric features. To reason about partial maps of novel, highly cluttered locations, hypotheses about significant structure in the disposition of free space may be used to guide exploration task assignment. A parsing of map data into places with semantic significance to the exploration task provides a foundation from which one may infer an efficient exploration strategy.