Energy-Aware Optimization of Multi-Robot Systems with Task Allocation and Partial Recharge Scheduling

This paper presents a task allocation and scheduling model for multi-robot systems operating under energy constraints. The proposed model integrates key factors such as energy consumption, battery charging management, and task execution efficiency. To address this problem, we employ both an exact solver-based method and a bio-inspired algorithm, enabling a comparative analysis of their performance in terms of solution quality and computational efficiency. Experimental results highlight the trade-offs between execution time, energy consumption, and task scheduling efficiency. These insights contribute to optimizing task scheduling in multi-robot systems while minimizing energy expenditure. Future research will investigate the impact of parameters such as speed, charging and discharging rates, the optimal number of charging stations, and the integration of nonlinear battery dynamics models.