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生物启发的预激活反射增加了在崎的地形上行走的强度
Elsa K Bunz1,2, Daniel F B Haeufle3,4,5, C David Remy6,5,7
1Institute for Modelling and Simulation of Biomechanical Systems, University of Stuttgart, Stuttgart, Germany. elsa.bunz@imsb.uni-stuttgart.de.
Scientific reports
|August 14, 2023
概括
人类肌肉预激活可以提高机器人在崎的地形上行走的稳定性. 通过将这种生物灵感策略添加到神经肌肉骨模型中,机器人可以更好地处理意想不到的下降干扰,而不需要检测它们.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 生物力学 生物力学
- 控制系统 控制系统
背景情况:
- 双脚机器人与崎的地形作斗争,与自然适应干扰的人类不同.
- 神经肌肉骨 (NMS) 模型是将人类控制策略转移到机器人的关键.
- 目前基于反射的NMS模型缺乏对意外环境变化的稳定性.
研究的目的:
- 通过结合类似人类的肌肉预激活策略来增强广泛使用的NMS步行模型的强度.
- 调查预激活对适应着陆和改善干扰期间稳定性的影响.
- 探索这种生物灵感的方法在具有挑战性的表面上进行机器人运动的潜力.
主要方法:
- 将肌肉预激活反循环集成到现有的基于反射的NMS行走模型中.
- 模拟了意想不到的降级干扰,以评估模型性能.
- 分析了膝盖动力学和整体系统强度的变化.
主要成果:
- 增强的NMS模型显示了对着陆的改进适应性.
- 对意想不到的降级干扰的强度显著增加,从3厘米增加到10厘米.
- 稳定效应归因于因预激活而导致的膝盖动力学变化.
结论:
- 肌肉预激活作为适应策略,增强稳定性,而没有明确的干扰检测.
- 这种生物灵感的反射适应可以显著提高双脚机器人在崎的地形上的性能.
- 预激活策略可以移植到机器人系统中,以增加对意外环境挑战的弹性.
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