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Distributed multi-vehicle task assignment in a time-invariant drift field with obstacles

机译:具有障碍的时不变漂移场中的分布式多车辆任务分配

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This study investigates the task assignment problem where a fleet of dispersed vehicles needs to visit multiple target locations in a time-invariant drift field with obstacles while trying to minimise the vehicles' total travel time. The vehicles have different capabilities, and each kind of vehicles can visit a certain type of the target locations; each target location might require to be visited more than once by different kinds of vehicles. The task assignment problem has been proven to be NP-hard. A path planning algorithm is first designed to minimise the time for a vehicle to travel between two given locations through the drift field while avoiding any obstacle. The path planning algorithm provides the travel cost matrix for the target assignment, and generates routes once the target locations are assigned to the vehicles. Then, a distributed algorithm is proposed to assign the target locations to the vehicles using only local communication. The algorithm guarantees that all the visiting demands of every target will be satisfied within a total travel time that is at worst twice of the optimal when the travel cost matrix is symmetric. Numerical simulations show that the algorithm can lead to solutions close to the optimal.
机译:这项研究调查了任务分配问题,其中分散的车队需要在具有障碍物的时不变漂移场中访问多个目标位置,同时尝试最小化车辆的总行驶时间。车辆具有不同的功能,每种车辆都可以访问特定类型的目标位置;每个目标位置可能需要由不同种类的车辆多次访问。任务分配问题已被证明是NP难的。首先设计路径规划算法,以使车辆在两个给定位置之间通过漂移场行驶的时间最小化,同时避免任何障碍物。路径规划算法为目标分配提供旅行成本矩阵,并在将目标位置分配给车辆后生成路线。然后,提出了一种分布式算法,仅使用本地通信将目标位置分配给车辆。该算法保证在旅行成本矩阵对称时,在总旅行时间内(这是最优旅行时间的最差值的两倍),可以满足每个目标的所有访问需求。数值仿真表明,该算法可以导致接近最优解。

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