Adaptive robotic gait control using coupled artificial signalling networks, hopf oscillators and inverse kinematics

Adaptive robotic gait control using coupled artificial signalling networks, hopf oscillators and inverse kinematics
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使用耦合人工信号网络、hopf 振荡器和逆运动学的自适应机器人步态控制

DOI:
10.1109/cec.2013.6557732
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发表时间:
2013
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--
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Fuente L
Fuente L
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为了利用环境信息产生自适应有节奏的运动模式,提出了一种新颖的仿生六足机器人结构,该结构包括三层结构。从解码环境信息的细胞内信令过程中得到启发,并考虑到多个信令路径相互作用产生的紧急行为,我们开发了一个由一组人工信令网络组成的分布式机器人控制器。串扰是一种生物信号机制,用于耦合有利于它们相互作用的网络。我们还将非线性振荡器应用于步态产生器的建模,这些步态产生器可以诱导对称且有节奏的运动。轨迹由一个耦合的人工信号网络进行调制,产生自适应和稳定的机器人运动模式。通过逆运动学方法将步态轨迹转化为关节角度。该体系结构在真实机器人T-Hex的模拟版本中实现。我们的结果证明了该体系结构能够生成自适应和周期性步态。
A novel bio-inspired architecture comprising three layers is introduced for a six-legged robot in order to generate adaptive rhythmic locomotion patterns using environmental information. Taking inspiration from the intracellular signalling processes that decode environmental information, and considering the emergent behaviours that arise from the interaction of multiple signalling pathways, we develop a decentralised robot controller composed of a collection of artificial signalling networks. Crosstalk, a biological signalling mechanism, is used to couple such networks favouring their interaction. We also apply nonlinear oscillators to model gait generators, which induce symmetric and rhythmical locomotion movements. The trajectories are modulated by a coupled artificial signalling network, which yields adaptive and stable robotic locomotive patterns. Gait trajectories are converted into joint angles by means of inverse kinematics. The architecture is implemented in a simulated version of the real robot T-Hex. Our results demonstrate the ability of the architecture to generate adaptive and periodic gaits.
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