Autonomous Intermuscular Coordination and Leg TrajectoryGeneration of Neurophysiology-based Quasi-quadruped Robot

Autonomous Intermuscular Coordination and Leg TrajectoryGeneration of Neurophysiology-based Quasi-quadruped Robot
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自主肌肉协调和腿部轨迹基于神经生理学的准四足机器人的生成

DOI:
10.1109/sii46433.2020.9025819
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发表时间:
2020
期刊:
2020 IEEE/SICE International Symposium on System Integration (SII)
影响因子:
--
通讯作者:
M. Ishikawa
M. Ishikawa
中科院分区:
--
文献类型:
--
作者:
Yoichi Masuda;M. Ishikawa

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在这项研究中,我们介绍了一个简单的自我控制的准四足机器人的灵感来自感觉反馈机制在后肢的去大脑行走四足动物。本文的主要贡献是表明,四足动物后肢与肌肉受体的模型可以协调其肌肉,并产生一个腿的轨迹没有任何中央模式发生器。产生四肢和肌肉协调模式的关键思想是基于无脑控制方法。该方法的一个要点是,致动器模块是嵌入式的,没有任何微处理器,也没有控制器。每个致动器模块根据从身体-环境动力学接收的反作用力使用它们的内在动力学来调整它们的相位,并且因此,协调的运动模式出现。本文中的机器人由人工气动肌肉驱动,仅由简单的反射电路控制,反射电路由机械空气阀组成,将气流切换到肌肉。因此,机器人不需要微处理器或步态发生器,并且机器人唯一需要的输入是由外部空气压缩机提供的恒定气压。步行实验演示了自主步态生成,我们比较了机器人和一个完整的猫之间的关节角度的时间序列。
In this study, we introduce a simple self-controlled quasi-quadruped robot inspired by sensory feedback mechanisms in the hindlimb of decerebrate walking quadrupeds. The main contribution of this paper is to show that a model of the quadruped hindlimb with muscle receptors can coordinate its muscles and generate a leg trajectory without any central pattern generators. The key idea to produce coordinated patterns of limbs and muscles is based on the brainless control approach. A point of the approach is that the actuator module is embedded without any microprocessors nor a controller. Each actuator module adjusts their phases using intrinsic dynamics of them according to the reaction force received from the body-environment dynamics and, as a result, coordinated motor patterns emerge. The robot in this article is driven by artificial pneumatic muscles and controlled by only simple reflex circuits composed of mechanical air valves that switch the airflow to the muscles. Therefore, the robot needs no microprocessors or gait generators, and the only required input for the robot is a constant air-pressure which is supplied from an external air compressor. A walking experiment demonstrates autonomous gait generation, and we compare the time series of joint angles between the robot and an intact cat.
使用振荡器网络的四足机器人视觉引导运动控制
DOI: --
发表时间: 2007
期刊:
影响因子: --
作者:
T. Aragi;T. Kimura;K. Tsujita;T. Masuda
通讯作者: T. Masuda
腿部机器人中跨越协调的自适应控制策略:审查。
DOI: 10.3389/fnbot.2017.00039
发表时间: 2017
影响因子: 3.1
作者:
Aoi S;Manoonpong P;Ambe Y;Matsuno F;Wörgötter F
通讯作者: Wörgötter F
DOI: 10.1177/027836499000900206
发表时间: 1990-04-01
影响因子: 9.2
作者:
MCGEER, T
通讯作者: MCGEER, T