探索软武器的建模技术:对数值,分析和数据驱动方法的调查
Shengkai Liu1, Hongfei Yu2, Ning Ding1,2
1Shenzhen Institute of Artificial Intelligence and Robotics for Society, Shenzhen 518000, China.
Biomimetics (Basel, Switzerland)
|February 25, 2025
概括
本综述探讨了软机器人手臂的建模策略,这对于可适应自动化和生物医学应用至关重要. 它分析了数值,分析和数据驱动的方法,以指导未来的软臂设计和控制.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 机械工程 机械工程
- 控制系统 控制系统
背景情况:
- 软臂提供了合规性和适应性,推动了对工业自动化和生物医学领域的兴趣.
- 模拟软臂是具有挑战性的,因为高度的自由度,非线性和复杂的材料特性.
研究的目的:
- 为软机器人手臂提供初级建模方法的全面概述.
- 分析不同建模技术的优点,局限性和应用.
- 引导研究人员选择和开发有效的建模策略.
主要方法:
- 对数值方法的审查 (例如,有限元分析,多体动力学).
- 基于连续力学分析分析技术的分析.
- 使用机器学习和人工智能探索数据驱动模型.
主要成果:
- 数字方法提供精度,但计算密集.
- 分析模型平衡了洞察力和计算效率.
- 数据驱动模型通过绕过显式物理来实现自适应的实时控制.
结论:
- 每种建模方法在软臂应用中都有明显的优点和缺点.
- 这些方法的整合是一个有希望的未来方向.
- 有效的建模对于推进软机器人手臂设计和控制至关重要.
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