对于在救援行动中使用异质机器人的群猎策略
Dileep Sivaraman1, Songpol Ongwattanakul1, Choladawan Moonjaita1
1Department of Biomedical Engineering, Center for Biomedical and Robotics Technology (BART LAB), Faculty of Engineering, Nakhon Pathom 73170, Thailand.
Bioinspiration & biomimetics
|December 13, 2024
概括
这项研究提高了机器人团队在救援行动中的协调,使用团队狩猎策略. 机器人可以动态地适应角色,提高复杂环境中的任务效率和资源管理.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 人工智能的人工智能
- 群集情报 群集情报 群集情报
背景情况:
- 协调异质机器人 (无人机,UGV) 对于复杂的任务,如救援行动至关重要.
- 现有的方法通常依赖于静态的角色,限制了在动态环境中的适应性.
研究的目的:
- 开发一个新的框架,以改善异质机器人团队的协调.
- 通过自适应机器人行为提高救援行动的有效性.
主要方法:
- 受到自然团伙狩猎策略的启发,开发了一个将等级决策与分散控制相结合的框架.
- 动态目标分配和实时任务分配使用多因素评分功能 (距离,能量,通信).
- 实现适应性"追逐者"和"侧翼者"角色,允许机器人根据实时数据进行切换.
主要成果:
- 拟议的框架显示出卓越的协调和决策能力.
- 机器人自主调整其角色以优化任务结果.
- 在模拟救援场景中提高响应能力和有效利用资源.
结论:
- 将层次结构与去中心化控制相结合,可以显著提高机器人团队的性能.
- 适应性角色交换机制提高了复杂,不断变化的环境中的适应性.
- 该框架显示了现实应用的巨大潜力,特别是在自主救援行动中.
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