An overview of Ant Colony Optimization (ACO) for Multiple-Robot Task Allocation (MRTA)

The multiple-robots are used for carrying out different tasks and they can be either stationary or mobile robots. Tasks can be discrete or continuous and it varies due to complexity and specificity. There are various approaches used for multiple robot task allocation (MRTA). This paper presents overview of application of Ant Colony Optimization (ACO) algorithm for multi-robot task allocation. The ant colony algorithm is mimic of ant's behavior with "simulated ants" walking around the graph representing the problem to solve. For this purpose, sample problems consisting of cost matrix for multiple robots and multiple tasks are formulated and evaluated by using ACO algorithm developed by using MATLAB software and compared with Conventional method. The sample problems are limited to symmetric condition just to validate the scope of ACO. The results show that, ant colony algorithm has a high degree of ability and reliability for solving MRTA.