A PSO based multi-robot task allocation Online publication date: Thu, 31-Mar-2011
by B.B. Choudhury, B.B. Biswal
International Journal of Computational Vision and Robotics (IJCVR), Vol. 2, No. 1, 2011
Abstract: Recent research trends and technology developments have been instrumental to the realisation of autonomous multi-robot systems (MRS) performing increasingly complex missions. However the selection of candidate robots from a team of robots for performing the task(s) from a set of desired tasks in order to achieve an economical and feasible process poses a difficult problem. Task distribution methodologies have to make sure that not only the global assignment is achieved, but also the tasks are well assigned among the robots. This paper presents the particle swarm optimisation (PSO) algorithm designed to address this problem. A two-phase solution methodology is used to solve the multi-robot task allocation (MRTA) problem wherein the task capability of the robots is determined during the first segment and the task allocation optimisation is done using PSO during the second segment. The solution to MRTA problem in dynamic environment is proposed using a novel PSO based algorithm and is compared with that using linear programming (LP).
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