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首页> 外文期刊>IEEE Transactions on Aerospace and Electronic Systems >Cooperative Aerial–Ground Vehicle Route Planning With Fuel Constraints for Coverage Applications
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Cooperative Aerial–Ground Vehicle Route Planning With Fuel Constraints for Coverage Applications

机译:合作空中地面车途规划,覆盖应用燃料限制

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Low-cost unmanned aerial vehicles (UAVs) need multiple refuels to accomplish large area coverage. We propose the use of a mobile ground vehicle (GV), constrained to travel on a given road network, as a refueling station for the UAV. Determining optimal routes for a UAV and GV, and selecting rendezvous locations for refueling to minimize coverage time is NP-hard. We develop a two-stage strategy for coupled route planning for UAV and GV to perform a coverage mission. The first-stage computes refueling sites that ensure reachability of all points of interest by the UAV and feasible routes for both the UAV and GV. In the second stage, mixed-integer linear programming (MILP) based exact methods are developed to plan optimal routes for the UAV and GV. As the problem is NP-Hard, we also develop computationally efficient heuristics that can find good feasible solutions within a given time limit. Extensive simulations are conducted to corroborate the effectiveness of the developed approaches. Field experiments are also performed to verify the performance of the UAV-GV solution.
机译:低成本无人机(无人机)需要多种摘要来完成大面积的覆盖范围。我们提出了使用移动地面车辆(GV),限制在给定的道路网络上旅行,作为无人机的加油站。确定UAV和GV的最佳路由,并选择用于最小化覆盖时间的Rendezvous位置是NP-Hard。我们为无人机和GV耦合路线规划开发了两阶段策略,以执行覆盖特派团。第一阶段计算加油站点,以确保无人机和无人机和GV的可行兴趣点的可达性。在第二阶段,开发了基于混合整数的线性编程(MILP)的精确方法,以计划UAV和GV的最佳路线。由于问题是NP - 硬,我们还开发了计算上的高效启发式,可以在给定的时间限制内找到良好的可行解决方案。进行广泛的模拟以证实发达方法的有效性。还执行现场实验以验证UAV-GV解决方案的性能。

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