The work addresses the optimisation of fleet management for mobile robots in agronomy. The research focuses on multi-agent coordination, task scheduling, and battery charging strategies. A flexible simulation environment has been developed to test various decision-making strategies, allowing changes to the number of robots, the configuration of the working area, and charging strategies. Experimental results show that increasing the number of robots does not always lead to a proportional increase in efficiency, due to scheduling conflicts and limited access to charging stations. The findings highlight the importance of optimising strategies for efficient fleet operation, and the simulation environment is an effective tool for developing and analysing management strategies in agronomic applications.
|
