Cooperative Route Planning for Fuel-constrained UGV-UAV Exploration

Mingjia Zhang, Huawei Liang, Pengfei Zhou
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引用次数: 1

Abstract

Heterogeneous UGV-UAV system can efficiently complete large-scale tasks such as exploration and rescue by collaborative operation. This paper proposes a route planner based on a dynamic aggregation strategy to select the time-optimal routes for function-constrained UGV and fuel-constrained UAV to reach all the mission points. To reduce the time consumption of waiting at the take-off point, UGV and UAV are inclined to rendezvous at the next meeting point by no-wait operations. We present a two-step routing strategy to address this cooperative problem. First, the Voronoi diagram and greedy set cover method are used to determine meeting points and task areas. Then, solving a traveling salesman problem to find a UGV path by A-star and Lin-Kernighan heuristic. After that, an adaptive large neighborhood search heuristic is proposed to address vehicle routing problem with recharge for UAV among multiple task areas. The simulation and real experiment results demonstrate that our approach can effectively generate a time-optimal path for UGV-UAV Cooperative exploration.
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燃油约束下UGV-UAV探索协同路径规划
异构UGV-UAV系统可以通过协同操作高效完成大规模的勘探、救援等任务。提出了一种基于动态聚合策略的路径规划方法,为功能受限的无人驾驶车和燃料受限的无人机选择时间最优的路径到达所有任务点。为了减少在起飞点等待的时间消耗,UGV和UAV倾向于通过不等待操作在下一个集合点集合。我们提出了一个两步路由策略来解决这个合作问题。首先,利用Voronoi图和贪心集覆盖法确定会议点和任务区域;然后,利用a -star启发式和Lin-Kernighan启发式求解旅行商寻找UGV路径的问题。在此基础上,提出了一种自适应大邻域搜索启发式算法来解决无人机在多任务区域间充值的车辆路径问题。仿真和实际实验结果表明,该方法可以有效地生成UGV-UAV协同探索的时间最优路径。
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