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相关概念视频

One-Degree-of-Freedom System01:24

One-Degree-of-Freedom System

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In mechanical engineering, one-degree-of-freedom systems form the basis of a wide range of electrical and mechanical components. Using these models, engineers can predict the behavior of various parts in a larger system, which gives them insight into how different forces interact with each other.
A one-degree-of-freedom system is defined by an independent variable that determines its state and behavior. One example of a one-degree-of-freedom system is a simple harmonic oscillator, such as a...
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Hierarchy of Motor Control01:18

Hierarchy of Motor Control

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The hierarchy of motor control refers to the different levels of organization and processing involved in controlling movement in the body. These levels range from higher cortical areas involved in planning and decision-making to lower spinal cord reflexes that respond automatically to external stimuli.
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Human-Inspired Dexterity-Oriented Perception and Trajectory Optimization for Robotic Surface Inspection.

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Correction: Yang et al. Flexible Model Predictive Control for Bounded Gait Generation in Humanoid Robots. <i>Biomimetics</i> 2025, <i>10</i>, 30.

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Sit-to-stand-and-walk from 120% Knee Height: A Novel Approach to Assess Dynamic Postural Control Independent of Lead-limb
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Sit-to-stand-and-walk from 120% Knee Height: A Novel Approach to Assess Dynamic Postural Control Independent of Lead-limb

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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
PubMed
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:

关键词:
灵活的C-T模型步行方式的世代.模型预测控制模型预测控制稳定的反转稳定反转.

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  • 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.