This wok describes novel algorithms for planning the deployment of a large number of navigationally-challenged mobile sensor nodes in known indoor environments. Due to cost and power constraints, our mobile sensor nodes have the ability to move and communicate, but they cannot detect or avoid obstacles or localize to the environment. Additionally, they have only minimal capabilities for detecting other robot team members, through the use of a crude camera. Our deployment process, therefore, uses an assistive navigation technique that enables a more capable leader robot, equipped with a laser rangefinder and a camera, to guide several mobile sensor nodes to their deployment positions. To ensure the successful deployment of the mobile sensor nodes, we have developed an autonomous planning process that plans the positions of the sensor nodes based upon a number of constraints, including maintaining line of sight maximizing visibility coverage, avoiding placement in doorways, minimizing obstruction of corridors, and so forth. Additionally, because of the navigational constraints of simple robots following a leader to these deployment positions, our algorithm also derives two leader waypoints for each sensor position, which on strain the motion of the leader path to the deployment position. These leader

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.