An Exact Algorithm for Task Allocation of Multiple Unmanned Surface Vehicles with Minimum Task Time

Kai Xue,Zhiqin Huang,Zeyu Xu,Ping Wang

doi:10.3390/jmse9080907

Kai Xue, Zhiqin Huang + Show 2 more

Open Access

https://doi.org/10.3390/jmse9080907

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Abstract

Task allocation of unmanned surface vehicles (USVs) with low task cost is an important research area which assigns USVs from starting points to different target points to complete tasks. Most of the research lines of task allocation are using heuristic algorithms to obtain suboptimal solutions to reduce both the max task cost and total task cost. In practice, reducing the maximum is more important to task time, which is from the departure of USVs to the last USV arriving at the designated position. In this paper, an exact algorithm is proposed to minimize the max task time and reduce the total task time based on the Hungarian algorithm. In this algorithm, task time is composed of the travel time along the planned path and the turning time at initial and target points. The fast marching square method (FMS) is used to plan the travel path with obstacle avoidance. The effectiveness and practicability of the proposed algorithm are verified by comparing it with the Hungarian algorithm (HA), the auction algorithm (AA), the genetic algorithm (GA) and the ant colony optimization algorithm (ACO). The results of path planning and task allocation are displayed in the simulation.

Highlights

Task allocation of multiple unmanned surface vehicles (USVs) is that a certain number of USVs at the initial points are allocated to the target points
Reducing the maximum is more important to task time which is from the departure of USVs to the last USV arriving at the designated position
In the task allocation of USVs, there is relatively little research that focuses on the exact algorithm of minimizing the max cost and reducing the total cost to obtain the optimal solution

Summary

Introduction

The optimal solution can be obtained at a certain computing time by exact algorithms They mainly focus on reducing the total task cost, such as the Hungarian algorithm [17]. An exact algorithm for task allocation of multiple USVs is proposed, which minimizes the max task time and reduces the total task time. It considers multi-USVs as real working applications, which are characterized by known maps, task time and collision avoidance. The result of task allocation with only (7) as the constraint condition may have multiple solutions, because it can only determine the relationship between one USV and one target point corresponding to the element of the max cost in the allocation plan. Adding (5) as a constraint can reduce the total cost and an optimal solution can be obtained

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