• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>International Conference on Unmanned Aircraft Systems >Cooperative route planning of multiple fuel-constrained Unmanned Aerial Vehicles with recharging on an Unmanned Ground Vehicle
【24h】

Cooperative route planning of multiple fuel-constrained Unmanned Aerial Vehicles with recharging on an Unmanned Ground Vehicle

机译：无人机地面车辆再充电多燃料约束无人机车辆的合作路线规划

获取原文
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Multiple small, low cost, multi-rotor Unmanned Aerial Vehicles (UAVs) are ideal for aerial surveillance over large areas. However, their limited battery capacity restricts them to areas in proximity of stationary recharging depots. One solution is to use an Unmanned Ground Vehicle (UGV) to provide a moving recharging depot. The problem is then to find the time-or energy-optimal paths for the multiple fuel-constrained UAVs to visit a set of mission points while being recharged by stopping at the UGV, whose path also needs to be determined. This is a combinatorial optimization problem that is computationally challenging, but may be solved relatively fast using heuristics. In this paper, we present two-level optimization that involves, (1) finding a UGV path by fixing waypoints using K-means and then formulating and solving a traveling salesman problem (TSP), and (2) finding paths for the multiple UAVs using a vehicle routing problem (VRP) formulation with capacity constraints, time windows, and dropped visits. We used constraint programming to solve these problems in less than a minute on a standard desktop computer for up to 25 mission points and 4 UAVs. Our main observation is that increasing the number of UAVs decreases the mission time and refueling stops, but does not decrease the total distance covered or total time taken.
机译：多重，低成本，多转子无人驾驶飞行器（无人机）是大区域空中监控的理想选择。然而，它们有限的电池容量将它们限制在静止充电仓库附近的区域。一种解决方案是使用无人的地面车辆（UGV）来提供移动的充电仓库。然后，该问题是在通过在UGV停止在UGV停止时，找到多个燃料受限的过滤器的时间或能量最佳路径访问一组任务点，而是需要确定其路径。这是一个组合优化问题，这是计算上具有挑战性的，但可以使用启发式来解决比较快。在本文中，我们呈现了两级优化，涉及（1）通过使用K-means来修复航点，然后在制定和解决旅行推销员问题（TSP）的航线上找到UGV路径，（2）找到多个无人机的路径使用具有容量约束，时间窗口和删除访问的车辆路由问题（VRP）配方。我们使用约束编程在不到一分钟的标准桌面计算机上解决这些问题，最多可达25个任命点和4个无人机。我们的主要观察是，增加无人机数量减少了任务时间和加油站，但不会降低所涵盖的总距离或所花费的总时间。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号