A Distributed Solution to the Multi-robot Task Allocation Problem Using Ant Colony Optimization and Bat Algorithm

Abstract

The multi-robot task allocation problem is a very active search field in autonomous multi-robot systems. It consists of three elements: (i) a set of tasks requiring some supports, (ii) a set of robots offering some supports and (iii) an objective function. The solution of such a problem is to assign tasks to robots, while optimizing the considered objective function. We consider search and rescue scenarios: tasks are survivors, robots are unmanned aerial vehicles and the objective function is to rescue the maximum number of survivors. We propose a fully distributed solution made up of the following two main steps: (i) the first step uses ant colony optimization to construct overlapping task bundles for each robot; and (ii) the second step uses bat algorithm to construct disjoint task bundles for each robot. This solution has been implemented using Java programming language and JADE multi-agent platform. Simulation results show the efficiency and scalability of our solution, in terms of makespan values; and the quality of our solution is very close to the quality of an optimal solution (the difference is only 3.17%), in terms of objective function.