Considering the dynamic environments where mechanical failures and/or ground-based threats take place, unmanned aerial vehicles (UAVs) may be lost when performing tasks. As such, designing path planning algorithms in such dynamic scenarios poses significant challenges. In this paper, we propose a cooperative path planning algorithm that is decentralized and adapts to the dynamic environments. This algorithm consists of two stages: in the static stage (i.e., before starting from the base station), the path planning is formulated as a mixed-integer linear program (MILP) problem that the optimal solutions can be obtained by specific solvers; in the dynamic stages (i.e., during UAVs' flight), task reassignment is adaptively conducted among surviving UAVs' cooperations once a UAV is lost. To evaluate the effectiveness of the proposed algorithm, we demonstrate its superior performance through simulations compared to centralized ones in terms of the ratio of mission completion and the total completion time.
['Mingsheng Gao', 'Jun Jiang', 'Ng Kien Ming', 'Teo Kwong Meng', 'Kim-Leng Poh']
Cooperative path planning for UAVs with UAV loss considerations