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UAV PATH PLANNING IN THE FRAMEWORK OF MILP-TROPICAL OPTIMIZATION

机译:米尔普 - 热带优化框架中的无人机路径规划

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This paper proposes a fast method for obtaining mathematically optimal trajectories for UAVs while avoiding collisions. A comparison of the proposed method with previously used Mixed Integer Linear Programming (MILP) to find the optimal collision-free path UAVs, aircraft, and spacecraft show the effectiveness and performance of this method. Here, the UAV path planning problem is formulated in the new framework named MILP-Tropical optimization that exploits tropical mathematics for obtaining solution and then casted in a novel branch-and-bound method. Various constraints including UAV dynamics are incorporated in the proposed Tropical framework and a solution methodology is presented. An extensive numerical study shows that the proposed method provides faster solution. The proposed technique can be extended to distributed control for multiple vehicles and multiple way-points.
机译:本文提出了一种快速方法,用于在避免碰撞时获得无人机的数学上最佳轨迹。所提出的方法与先前使用的混合整数线性编程(MILP)的比较,以找到最佳的无碰撞路径无人机,飞机和航天器,显示了这种方法的有效性和性能。在这里,UAV路径规划问题在名为MILP-Tropical优化的新框架中制定了利用热带数学获得解决方案,然后以新颖的分支和拟合方法铸造。在所提出的热带框架中并入包括UAV动态的各种约束,并提出了解决方案方法。广泛的数值研究表明,所提出的方法提供更快的解决方案。所提出的技术可以扩展到多个车辆和多种方式点的分布式控制。

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