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相关实验视频

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通过参数自适应策略,基于微刺激的路径跟踪控制子机器人.

Yinggang Huang1,2, Lifang Yang1,2, Long Yang1,2

  • 1School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou 450001, China.

Heliyon
|October 10, 2024
PubMed
概括

这项研究引入了一个参数适应性策略,用于使用神经电刺激在动物机器人中精确的路径跟踪. 开发的系统在引导子机器人方面实现了82.165%的控制效率.

关键词:
行为预先控制.参数适应性战略的参数路径跟踪控制的控制方法子机器人子机器人刺激模型是一个刺激模型.

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科学领域:

  • 神经控制可以进行神经控制.
  • 机器人技术 机器人技术 机器人技术
  • 生物启发的工程是生物启发的.

背景情况:

  • 使用神经电刺激对动物机器人进行精确的行为控制是具有挑战性的.
  • 现有的方法缺乏对环境因素的动态适应.

研究的目的:

  • 开发一个参数适应性策略,以准确跟踪机器人的路径.
  • 量化神经刺激参数与行为反应之间的关系.
  • 为了增强自主系统的神经控制能力.

主要方法:

  • 量化的神经电刺激参数-行为反应映射.
  • 为参数适应性控制策略制定了调整规则.
  • 使用模糊控制原则设计了一个参数适应路径跟踪控制策略 (PAPTCS).

主要成果:

  • 改变刺激参数显著影响子机器人转角度.
  • 较高的UPN和PTN水平引起了运动状态的显著变化.
  • 在实验中,PAPTCS的平均控制效率为82.165%.

结论:

  • 参数适应性策略使子机器人能够精确地跟踪路径.
  • 这项研究为控制动物机器人的行为提供了一个参考.
  • 这些发现有助于精确目标路径跟踪技术的进步.