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相关概念视频

One-Degree-of-Freedom System01:24

One-Degree-of-Freedom System

517
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...
517

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相关实验视频

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3D Kinematic Gait Analysis for Preclinical Studies in Rodents
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深度学习视觉系统用于四肢机器人步行模式调节

Christyan Cruz Ulloa1, Lourdes Sánchez1, Jaime Del Cerro1

  • 1Centro de Automática y Robótica (CSIC-UPM), Universidad Politécnica de Madrid-Consejo Superior de Investigaciones Científicas, 28006 Madrid, Spain.

Biomimetics (Basel, Switzerland)
|July 28, 2023
PubMed
概括

这项研究介绍了一种适应式步行系统,用于四足机器人驾驶具有挑战性的地形. 该方法使用人工智能进行地形分析和步态调节,在克服障碍物方面取得了超过91%的成功.

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
  • 生物启发系统 生物启发系统

背景情况:

  • 四肢机器人越来越多地用于非结构化环境中的任务,如搜救.
  • 适应机器人的地形运动对于任务的成功至关重要,模仿动物的自然行为.
  • 人工智能增强了机器人特定地形的运动能力.

研究的目的:

  • 为四足机器人ARTU-R (A1救援任务UPM机器人) 开发一种适应步态模式方法,以克服非结构化的地形.
  • 将中央模式生成器 (CPG) 与卷积神经网络 (CNN) 集成,用于地形识别和障碍物表征.
  • 通过模拟和现实世界户外测试来验证拟议的方法.

主要方法:

  • 对狗的步态模式进行了一项研究,以告知基于CPG的运动系统.
  • 卷积神经网络用于自动地形识别和障碍物分析 (数量,大小,位置,超越能力).
  • 该方法在转移到真正的ARTU-R机器人之前,在ROS-Gazebo模拟中使用机器人模型进行了验证.

主要成果:

  • 拟议的方法在地形特征,包括识别,细分和障碍分析方面实现了超过93%的效率.
  • 该系统的成功率超过91%,使机器人能够克服非结构化的地形.
关键词:
生物启发的机器人技术卷积神经网络是一种卷积神经网络.四足机器人是四足的机器人机器人视觉机器人视觉转移学习转移学习

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  • 性能与最先进的发展和现有模型进行了基准测试.

    • 结论:

    • 开发的方法有效地使四足机器人能够适应他们的步态,以导航复杂的,非结构化的地形.
    • 人工智能驱动的地形分析和基于CPG的机动系统显著提高了机器人在具有挑战性的环境中的性能.
    • 这项研究有助于推进机器人的自主能力在现实世界的应用程序,如搜索和救援.