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Synthesis of Neural Oscillator based Dynamic Rhythmic Generation in Quadruped Robot Locomotion

机译:基于Quadruped Robot Locomotion基于神经振荡器的神经振荡器的合成

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This paper proposes motion pattern generation based sensory motor coordination in quadruped robot. Quadruped animal generates their motion pattern dynamically in every level of speed. The proposed locomotion model implements combined sensory motor coordination system as the dynamic walking pattern generation and polynomial equation as the swinging model in Cartesian level. In the sensory motor coordination model, motor neural oscillator as the rhythmic signal generator will be interconnected with internal sensory neurons, which composed by ground touch sensors in the sole of feet and body pose movement sensor (Inertial Measurement Unit). In order to optimized the interconnection structure between sensory neurons and motor neurons, we used multi-objective evolutionary algorithm. Error of desired walking and energy required is minimized as fitness function. In order to prove the effectiveness of the model, we implemented it in computer simulation and in proposed Felidae-like quadruped robot. The proposed model succeeded generate dynamic motion pattern in different movement speed. The proposed model has similarity motion pattern with animal gait in certain movement speed. The movement changing behavior depending on the changes of desired velocity are also shown.
机译:本文提出了四足机器人的运动模式生成的感觉电机协调。四足动物在每种速度下动态产生运动模式。所提出的运动模型将组合的感官电动机协调系统作为动态行走模式生成和多项式方程作为笛卡尔级的摆动模型。在感官电动机协调模型中,电动机神经振荡器作为节奏信号发生器将与内部感官神经元相互连接,该内部感官神经元由脚底和身体姿势运动传感器(惯性测量单元)的地触摸传感器组成。为了优化感觉神经元和电机神经元之间的互连结构,我们使用了多目标进化算法。所需步行的误差和所需的能量被最小化为健身功能。为了证明模型的有效性,我们在计算机模拟中实施了它,并在提出的Felidae样式机器人中实现。所提出的模型成功以不同的运动速度产生动态运动模式。所提出的模型具有在某些运动速度下具有动物步态的相似性运动模式。还示出了根据所需速度的变化的运动改变行为。

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