Task Allocation Optimization with Energy-Time Trade-off in Multi-Mobile Robot Systems

This study presents an engineering approach to the task assignment problem in multi-mobile robot automation systems based on energy and time criteria. Tasks are distributed by considering the physical characteristics of the robots, their distances to task points, task completion durations, and energy consumption, providing a comprehensive framework for system-level optimization. Assuming a static environment, path planning is performed using the A* algorithm to enable a more realistic estimation of travel distances, which is crucial for precise control and planning in robotics applications. Task assignments are executed through the Hungarian algorithm and suitable solution strategies by constructing a cost matrix based on energy and time. The proposed system was first validated in MATLAB and then tested in realistic robotic simulations using ROS and Gazebo. Furthermore, a flexible cost structure is proposed in which either the time or energy coefficient can be emphasized depending on the urgency of the task, and the adaptability of this structure to different scenarios is demonstrated. The presented method aims to optimize task planning in multi-robot systems in terms of either energy efficiency or task completion time, depending on user requirements.