Multi-objective UAV path planning for search and rescue

We propose a multi-objective optimization algorithm to allocate tasks and plan paths for a team of UAVs. The UAVs must find a target in a bounded area and then continuously communicate the target information to the ground personnel. Our genetic algorithm approach aims to minimize the mission completion time, which includes the time to find the target (area coverage) and the time to setup a communication path (network connectivity). We evaluate strategies using a data mule, a relay chain, and a novel hybrid approach to communicate with the ground personnel. The algorithm can be tuned to prioritize coverage or connectivity, depending on the mission demands. Simulation results show reduced overall mission completion times (up to 65%), with more improvement as the UAV density increases.