Multi-Vehicle Motion Planning for Search and Tracking

Abstract

We present a vision-based search and rescue system which uses a unmanned aerial vehicle(UAV) swarm to search and track missing personnel/animals. A major benefit of multiple-vehicle search operation is the extended coverage due to the "bridging" effect between the vehicles, which allow a larger and further search area that is beyond the reach of a single vehicle. The challenge here is to plan the UAV swarm's motion paths while maintain the communication links between vehicles during the flight. Our path planning method uses a two-tie search algorithm to approximate the optimum paths for n-UAV search. The integrated vision pipeline and target recognition subsystem is evaluated with emulated UAVs and image sensors.