Authors: B.B. Choudhury, B.B. Biswal
Addresses: Department of Mechanical Engineering, Indira Gandhi Institute of Technology, Sarang – 759146, Orissa, India. ' Department of Mechanical Engineering, National Institute of Technology Rourkela, Rourkela – 769008, Orissa, India
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).
Keywords: multi-robot tasks; task allocation; MRTA; multi-robot systems; particle swarm optimisation; PSO; linear programming; multiple robots.
International Journal of Computational Vision and Robotics, 2011 Vol.2 No.1, pp.49 - 61
Published online: 31 Mar 2011 *Full-text access for editors Access for subscribers Purchase this article Comment on this article