Semantically-informed coordinated multirobot exploration of relevant areas in search and rescue settings

Abstract

Coordinated multirobot exploration involves autonomous discovering of unknown features in environments by using multiple robots. Autonomously exploring mobile robots are driven by knowledge of the already explored portions of the environment, usually represented in a metric map. In the literature, some works addressed the use of semantic knowledge in exploration, which, embedded in a semantic map, associates spatial concepts (like `rooms' and `corridors') with metric entities, showing its effectiveness to improve total explored area. In this paper, we build on these results and propose a system that exploits semantic information to push robots to explore areas that are relevant, according to a priori information provided by human users. We tested our semantic-based multirobot exploration system in a reliable robot simulator and evaluated its performance in realistic search and rescue settings with respect to state-of-the-art approaches.