通过在线适应布尔网络机器人的故障恢复
Paolo Baldini1, Michele Braccini1, Andrea Roli1,2
1Department of Computer Science and Engineering (DISI), Alma Mater Studiorum-Università di Bologna, Campus of Cesena, 47521 Cesena, Italy.
Sensors (Basel, Switzerland)
|September 27, 2025
概括
机器人现在可以通过在线适应自动恢复损坏. 这种方法实时修改机器人控制策略,使故障恢复比从头开始更快.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 控制工程 控制工程 控制工程
- 人工智能的人工智能
背景情况:
- 故障恢复对于机器人的可靠性和运营连续性至关重要.
- 目前用于机器人故障恢复的方法通常涉及复杂的手动调整.
- 机器人技术中对自动化,实时适应策略的需求正在增加.
研究的目的:
- 调查在线适应自动机器人故障恢复的有效性.
- 开发一种方法,在运行时修改机器人控制策略,以克服故障.
- 确定机器人系统在线成功适应的技术要求.
主要方法:
- 使用性能函数来识别无效的机器人行为.
- 实施在线适应作为控制策略运行时修改机制.
- 比较现有控制器的调整与从头开始寻找新的控制器.
主要成果:
- 在线适应证明适合在机器人损坏后自动恢复功能.
- 调整现有的控制器以克服故障比设计一个新的要快得多.
- 该研究概述了成功实施在线适应的技术先决条件.
结论:
- 在线适应为机器人故障耐受性提供了高效和自动化的解决方案.
- 控制策略的运行时间修改提高了机器人的弹性,减少了停机时间.
- 与传统方法相比,这种方法可以加快恢复过程.
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