Strategies of division of labour for improving task efficiency in multi-robot systems

This paper addresses the issue of allocating tasks in multi-robot systems and evaluates the strategies that various ant colonies display in carrying out tasks and proposes four different task allocation strategies within the realms of multi-robot systems. The paper also introduces the concept of cost-benefit ratio as a measure of performance index for the task allocation strategies identified. Experimental results show that uniformly distributed specialised workers are better than generalised workers in carrying out tasks. The paper then improves the performance of the strategies by incorporating a long term memory to carry out tasks. The proposed model for task allocation is highly efficient, accurate and consistent with the biological counterparts. The model offers benefits in designing efficient multi-robot systems that can carry out more than one task.