在人形机器人中,灵活的模型预测控制用于有限的步态生成
Tianbo Yang1, Yuchuang Tong1, Zhengtao Zhang1
1Institute of Automation, Chinese Academy of Sciences, Beijing 100089, China.
Biomimetics (Basel, Switzerland)
|January 24, 2025
概括
人形机器人需要有界的步态来保持稳定. 一个新的灵活模型预测控制 (FMPC) 框架使用增强的灵活模型和约束来确保稳定,有界的运动,在模拟和真实机器人中得到验证.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 控制系统 控制系统
- 人类类型的机动车.
背景情况:
- 传统的模型预测控制 (MPC) 方法使用线性反转 (LIP) 或车表 (C-T) 模型对于具有灵活关节的机器人来说是不够的.
- 在复杂的环境中实现稳定的双脚运动需要有界的步态.
研究的目的:
- 为人形机器人提出灵活模型预测控制 (FMPC) 框架.
- 通过结合关节动力学和先进的约束来实现稳定和有限的步态控制.
主要方法:
- 开发了一个增强的灵活的Cart-Table (C-T) 模型,具有弹性层和辅助质量中心 (CoM).
- 集成零动量点 (ZMP) 速度作为控制变量.
- 制定了一个二次编程 (QP) 问题,用于有限的CoM轨迹的CoM,边界和ZMP约束.
主要成果:
- 在各种模拟条件下,FMPC框架成功生成了有限的CoM/ZMP轨迹.
- 模拟证明了该方法能够提高灵活的人形机器人的步态控制和稳定性.
- 在CASBOT和Openloong机器人上的验证证实了该方法的有效性和稳定性.
结论:
- 拟议的FMPC框架有效地解决了灵活的人类机器人的传统MPC的局限性.
- 该方法增强了稳定性,并在各种操作场景中实现了有限的步态控制.
- FMPC方法显示了改善人形机器人运动和现实世界的应用能力的巨大潜力.
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