Multi-mission path re-planning for multiple unmanned aerial vehicles based on unexpected events

Natural disasters such as forest fires, earthquakes, tsunamis, floods, hurricanes, and cyclones happen unexpectedly and bring out the worst influence on people. Unmanned Aerial Vehicles (UAVs) could be used under these disasters for surveillance, search and rescue. In order to have good performances in mission areas, effective algorithms are required in mission re-tasking and path re-planning to handle unanticipated events or any environmental disturbances. In this paper, a new algorithm is proposed to deal with path replanning for multi-mission of multi-UAV under environments with unexpected events. A group of UAVs are considered to perform joint missions. Each UAV plans its own initial, optimal or sub-optimal path using Voronoi graph and Dijkstra algorithm. Our algorithm is then employed to assign a distinct task to each UAV and to re-plan its path based on new multimission requirement corresponding to some unexpected events. In addition to a theoretical analysis of the algorithm, the paper has also provided relevant simulation results which have shown that the algorithm can be used effectively for multiple cooperating UAVs' path re-planning under uncertain and dynamic disaster environments.