用智能体模拟优化无人机群充电，提升物联网环境下的作业效率
Agent-based Simulation for Drone Charging in an Internet of Things Environment System
- 构建基于智能体的仿真模型，实现无人机群自主充电协调
- 在智慧农场场景中，显著降低电池耗尽风险，提升任务完成率
- 结合机器学习分析仿真敏感度，适合工业4.0与智慧农业研究者
本文提出一种基于智能体的仿真模型，用于协调无人机群在物联网（IoT）和工业4.0环境中的电池充电问题。模型详细描述了仿真方法、系统架构与实现过程。一个实际应用案例为智慧农场，展示了自主协调策略如何优化大规模无人机部署中的电池使用与任务效率。研究采用机器学习技术分析智能体仿真敏感度分析的输出结果，验证了模型的有效性与鲁棒性。
原文摘要 · Abstract (English)
This paper presents an agent-based simulation model for coordinating battery recharging in drone swarms, focusing on applications in Internet of Things (IoT) and Industry 4.0 environments. The proposed model includes a detailed description of the simulation methodology, system architecture, and implementation. One practical use case is explored: Smart Farming, highlighting how autonomous coordination strategies can optimize battery usage and mission efficiency in large-scale drone deployments. This work uses a machine learning technique to analyze the agent-based simulation sensitivity analysis output results.
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