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An Improved Algorithm for Constrained Multirobot Task Allocation in Cooperative Robot Tasks

机译:合作机器人任务中约束多机罗任务分配的改进算法

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This paper presents an improved algorithm for solving the complex task allocation problem in constrained multiple robot cooperative tasks. The existing multiple robot task allocation mechanisms do not discuss much about complex tasks, instead they treat tasks as simple, indivisible entities. Complex tasks are tasks that can be decomposed into a set of subtasks and so can be executed by several possible ways. The goal of cooperative task allocation algorithm for multiple mobile robots is to find which robot should execute which task in order to maximize the global efficiency and minimize the cost. Some factors such as benefit, cost, resources, and time should be considered during the course of task allocation. The meta-heuristic algorithm proposed here solves the task allocation problems with the characteristics like each task requires a certain amount of resources and each robot has a finite capacity of resource to be shared between the tasks it is assigned. The cost of solution which includes static costs when using robots, assignment cost, and communication cost between the tasks if they are assigned to different robots are also taken into account in developing the solution. A peer search scheme algorithm for solving the constrained task allocation problem is presented. Computational experiments using this algorithm have shown that the proposed method is superior in terms of computation time and solution quality.
机译:本文提出了一种改进算法,用于解决受约束多机器人协作任务中的复杂任务分配问题。现有的多个机器人任务分配机制不讨论复杂任务,而是将任务视为简单,不可分割的实体。复杂任务是可以将其分解成一组子特许的任务,因此可以通过几种可能的方式执行。多个移动机器人合作任务分配算法的目标是找到哪些机器人应该执行哪个任务,以便最大化全局效率并最小化成本。在任务分配过程中,应考虑诸如福利,成本,资源和时间等因素。这里提出的元启发式算法解决了与每个任务的特征的任务分配问题需要一定量的资源,并且每个机器人都有有限容量在其分配的任务之间共享的资源。在开发解决方案时,还考虑了在任务之间使用机器人,分配成本和任务之间的通信成本时,包括静态成本的成本。介绍了用于解决受约束任务分配问题的对等搜索方案算法。使用该算法的计算实验表明,所提出的方法在计算时间和解决方案质量方面优越。

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