An improved algorithm for constrained multirobot task allocation in cooperative robot tasks

Abstract

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. © 2011 Springer Science+Business Media B.V.