Heuristic based Task Allocation Algorithm for Multiple Robots Using Agents

Task allocation plays an important role in achieving high utilization of robots in multiple robots system. Existing task allocation schemes do not consider the dynamic and unpredictable nature of the environment and try to maximize the robot synergism in order to achieve various objectives such as minimization of turnaround time, make span, and cost. Here the methodology for task allocation using a set of static and mobile agents controlling a pool of multiple robots is presented and the objective is to minimize the turnaround time. The agents are capable of autonomous decision making and thus make autonomous task allocation decisions based on the changing status of the robot system. Also, the agents are used for delivering the task and collecting the results in two separate trips thus avoiding the waiting time, which in turn helps to minimize the turnaround time. The performance of the algorithm is assessed by comparing with other existing task allocation method. The numerical simulation results manifest that the proposed algorithm performs the best under different problem scales and connectivity.