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Integration of multi sensors for adaptive walking of a quadruped robot

机译:集成了多个传感器,用于四足机器人的自适应行走

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We have been trying to induce a quadruped robot to walk with medium walking speed on irregular terrain based on biological concepts. A PD-controller at joints constructs virtual spring-damper systems as the visco-elasticity model of a muscle. The neural system model consists of a CPG (central pattern generator) and reflexes. A CPG receives sensory input and changes the period of its own active phase. The desired angle and P-gain of each joint in the virtual spring-damper systems is switched based on the phase signal of the CPG. CPGs , the motion of the virtual spring-damper system of each leg and the rolling motion of the body are mutually entrained through rolling motion feedback to CPGs, and can generate adaptive walking. The adaptation on irregular terrain based on multi sensors including vision is integrated in the neural system centering the CPGs. MPEG footage of these experiments can be seen at: http://www.kimura.is.uec.ac.jp.
机译:我们一直试图基于生物学概念,使四足机器人在不规则地形上以中等步行速度行走。关节处的PD控制器构造虚拟的弹簧阻尼器系统,作为肌肉的粘弹性模型。神经系统模型由CPG(中央模式生成器)和反射组成。 CPG接收感觉输入并更改其自己的活动阶段的周期。虚拟弹簧阻尼器系统中每个关节的期望角度和P增益基于CPG的相位信号进行切换。 CPG,每条腿的虚拟弹簧阻尼器系统的运动与身体的滚动运动通过对CPG的滚动运动反馈而相互夹带,并可以产生自适应步行。基于多传感器(包括视觉)的不规则地形的适应性集成在以CPG为中心的神经系统中。这些实验的MPEG素材可在以下网址查看:http://www.kimura.is.uec.ac.jp。

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