Indoor target intercept using an acoustic sensor network and dual wavefront path planning

Abstract

This paper presents an approach that enables a mobile "interceptor" robot to intercept targets in an indoor environment using information from a distributed acoustic sensor network. The approach assumes the indoor environment has been previously mapped and that the sensor nodes know their position in the map. The targets are localized in the sensor network based upon local maxima of the acoustic volume. The current target localization information is reported to an interceptor robot, which utilizes a dual wavefront path planner to move from its current location to a location that is within visibility range of a target. Results of the complete implementation of this approach using 70 sensor net robots in the player/stage multi-robot simulator are reported, as well as implementation results to date on a team of physical robots. To our knowledge, this is the first implementation of a multi-robot system that combines the use of an acoustic sensor net for target detection with an interceptor robot that can efficiently reach the moving position of the detected target in indoor environments.