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In the context of search and rescue, we consider the problem of missionplanning for heterogeneous teams that can include human, robotic, and animalagents. The problem is tackled using a mixed integer mathematical programmingformulation that jointly determines the path and the activity scheduling ofeach agent in the team. Based on the mathematical formulation, we propose theuse of soft constraints and penalties that allow the flexible strategic controlof spatio-temporal relations among the search trajectories of the agents. Inthis way, we can enable the mission planner to obtain solutions that maximizethe area coverage and, at the same time, control the spatial proximity amongthe agents (e.g., to minimize mutual task interference, or to promote localcooperation and data sharing). Through simulation experiments, we show theapplication of the strategic framework considering a number of scenarios ofinterest for real-world search and rescue missions.

Strategic Control of Proximity Relationships in Heterogeneous Search and Rescue Teams