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Coordinated road-network search route planning by a team of UAVs

机译:无人机团队协调的路网搜索路线规划

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This paper presents a road-network search route planning algorithm by which multiple autonomous vehicles are able to efficiently visit every road identified in the map in the context of the Chinese postman problem. Since the typical Chinese postman algorithm can be applied solely to a connected road-network in which ground vehicles are involved, it is modified to be used for a general type of road map including unconnected roads as well as the operational and physical constraints of unmanned aerial vehicles (UAVs). For this, a multi-choice multi-dimensional knapsack problem is formulated to find an optimal solution minimising flight time and then solved via mixed integer linear programming. To deal with the dynamic constraints of the UAVs, the Dubins theory is used for path generation. In particular, a circular-circular-circular type of the Dubins path is exploited based on a differential geometry to guarantee that the vehicles follow the road precisely in a densely distributed road environment. Moreover, to overcome the computational burden of the multi-choice multi-dimensional knapsack algorithm, a nearest insertion and auction-based approximation algorithm is newly introduced. The properties and performance of the proposed algorithm are evaluated via numerical simulations operating on a real village map and randomly generated maps with different parameters.
机译:本文提出了一种路网搜索路线规划算法,在中国邮递员问题的背景下,多辆自动驾驶汽车能够有效访问地图中标识的每条道路。由于典型的中国邮递员算法仅可应用于涉及地面车辆的连接道路网络,因此将其修改后可用于一般类型的路线图,包括未连接道路以及无人驾驶飞机的操作和物理约束车辆(UAV)。为此,制定了一个多选择多维背包问题,以找到使飞行时间最小化的最佳解决方案,然后通过混合整数线性规划进行求解。为了应对无人机的动态约束,将杜宾斯理论用于路径生成。特别地,基于微分几何学开发了Dubins路径的圆-圆-圆-圆形类型,以确保车辆在密集分布的道路环境中精确地沿着道路行驶。此外,为了克服多选择多维背包算法的计算负担,新引入了基于最近插入和拍卖的近似算法。通过对真实村庄地图和随机生成的具有不同参数的地图进行数值模拟,评估了所提出算法的性能和性能。

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