基于安全联系的机器人使用贝叶斯优化和控制屏障函数进行主动搜索
Frederik Vinter-Hviid1, Christoffer Sloth2, Thiusius Rajeeth Savarimuthu1,2
1ROPCA ApS, Odense, Denmark.
Frontiers in robotics and AI
|May 14, 2024
概括
本研究介绍了使用贝叶斯优化和控制障碍函数对自主机器人的安全主动搜索. 该方法增强了对类风湿性关节炎的超声波扫描,同时通过限制接触力来确保患者的安全.
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
- 医疗成像医学成像
背景情况:
- 对于机器人在不确定的环境中进行安全探索至关重要,以防止损坏.
- 自主超声波扫描需要精确的导航和可控的交互.
研究的目的:
- 为自主机器人开发安全的积极搜索方法.
- 确保患者安全,改善医疗机器人应用中的图像质量.
主要方法:
- 使用贝叶斯优化与信息化的持续预期改进获取函数.
- 实施指数控制屏障函数来绑定机器人环境接触力.
- 在接触模型中利用力导数来提高强度.
主要成果:
- 在有限的时间内 (60岁以下) 实现了92%的积极搜索成功率,比标准预期改进提高了13%.
- 成功地将机器人的接触力限制在5N以下,即使接触边界规格不准确.
- 在一个自主机器人上安全主动搜索的首次演示,用于类风湿性关节炎超声波扫描.
结论:
- 拟议的方法可以在不确定的环境中实现安全和高效的自主机器人操作.
- 控制屏障功能有效地确保了医疗机器人的安全性和稳定性.
- 这种方法显著提高了主动搜索性能,并保证了患者的安全.
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