Optimal deployment of robotic teams for autonomous wilderness search and rescue

This paper presents a novel method for the optimal deployment of multi-robot teams for autonomous, coordinated wilderness search and rescue. The new concept of iso-probability curves, used to represent the time-varying prediction of a lost person's probable location within the search area, is utilized to effectively distribute the search effort. The proposed method can be used for initial deployment, as well as subsequent on-line re-deployment to address the dynamic nature of the search for a moving lost person in a growing search area with varying terrain. The modularity of the proposed method allows the user to define and utilize different objective functions and weigh them according to the goal at hand. The two specific objective functions considered in this paper are (minimizing) search time and (maximizing) the probability of success. A simulated realistic wilderness search scenario demonstrates the integration of optimal deployment within the overall search methodology.