Minimal Time Dynamic Task Allocation for a Swarm of Robots

Maha A. Alshawi 1 and Mohamed B. Shalan 2
1. AUC/Robotics, Control and Smart System Department, Cairo, Egypt
2. AUC/Computer Science Department, Cairo, Egypt
Abstract—This paper discusses a solution to one of the key issues in the swarm robotics field which is the dynamic task allocation problem in which a group of robots needs to be allocated to a set of tasks scattered in the environment in an efficient and decentralized way. The application considered in this context is the foraging application which can be addressed as a searching job followed by a transportation job. The near-optimal allocation scheme is found by using the Particle swarm optimization (PSO) technique to handle the whole task execution in a minimal time. Two case studies have been considered using different swarm sizes and the implemented code has been executed for a distinctive number of iterations. A stability proof for the PSO technique’s parameters choices is presented. Simulation results were verified by comparing the proposed algorithm with the simulated annealing optimization technique in terms of computational time, number of iterations needed and quality of solution to demonstrate the robustness and efficiency of the algorithm. 

Index Terms—dynamic task allocation, swarm robotics, particle swarm optimization, simulated annealing, swarm optimization, homogeneous robots.

Cite: Maha A. Alshawi and Mohamed B. Shalan, "Minimal Time Dynamic Task Allocation for a Swarm of Robots," International Journal of Mechanical Engineering and Robotics Research, Vol. 6, No. 6, pp. 481-487, November 2017. DOI: 10.18178/ijmerr.6.6.481-487
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