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Nearest neighbour based task allocation with multi-agent path planning in dynamic environments

机译:基于最近的基于邻的任务​​分配,在动态环境中使用多代理路径规划

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This paper presents an effective solution to the task assignment problem combined with path planning using a group of autonomous agents. In this approach, path planning is incorporated with the task assignment; where agents start to move once the overall task is given. The main contribution of the proposed method is that it can effectively solve the task allocation problem in a distributed manner (among the agents). In this line, the other contribution of the paper is that it can effectively plan an optimum path by avoiding any types of collisions. Moreover, this method is capable of dealing with dynamic environments. The total methodology is based on the Particle Swarm Optimization (PSO) algorithm and for task allocation purposes the nearest neighbour search, approach is implemented. Following this approach, autonomous agents can successfully complete their mission in complex environments. The simulation results validate the proposed solution in dynamic environments.
机译:本文介绍了任务分配问题的有效解决方案与使用一组自主代理的路径规划相结合。在这种方法中,路径规划包含在任务分配中;一旦给出了整体任务,代理开始移动的地方。所提出的方法的主要贡献是,它可以以分布式方式(代理商中)有效地解决任务分配问题。在这一行中,纸张的其他贡献是它可以通过避免任何类型的碰撞来有效地规划最佳路径。此外,该方法能够处理动态环境。总方法基于粒子群优化(PSO)算法,并且对于任务分配目的是最近的邻居搜索,实现方法。在这种方法之后,自治代理可以成功完成复杂环境中的任务。仿真结果验证了动态环境中提出的解决方案。

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