Owing to flexibility and low cost, omnidirectional coverage on multi-target based on cooperative Unmanned Aerial Vehicles (UAVs) becomes attractive in surveillance mission recently. Although the camera technology has developed rapidly, it still faces challenges in omnidirectional coverage because of constraints on photographing ability of onboard camera sensors. First, due to inherent errors of camera sensors, the same target has to be covered by different UAVs to avoid large accumulated coverage error. Second, since the routes circling targets are modeled into regular polygons with different number of sides, the numbers of UAVs covering different targets is required to be different. Finally, the flight duration of UAV is limited since the onboard energy has a limitation. In this paper, to complete multi-target omnidirectional coverage mission in fair-energy fashion, we aim at planning trajectories for UAVs to minimize the maximum energy consumption. We propose a two-stage heuristic algorithm, in which we first adjust genetic algorithm to allocate targets to UAVs and then use a greedy algorithm to allocate polygon sides to UAVs. Compared with other algorithms, extensive simulations show that the proposed algorithm can reduce up to 16.2% and 13.2% in terms of maximum and average energy consumption, respectively.
Fair-energy trajectory plan for multi-target omnidirectional coverage based on cooperative UAVs
2019-11-01
721244 byte
Conference paper
Electronic Resource
English
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