A Neural Primitive model with Sensorimotor Coordination for Dynamic Quadruped Locomotion with Malfunction Compensation
A Neural Primitive model with Sensorimotor Coordination for Dynamic Quadruped Locomotion with Malfunction Compensation
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DOI：
10.1109/iros45743.2020.9340707
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发表时间：
2020-10
期刊：
影响因子：
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通讯作者：
Azhar Aulia Saputra;A. Ijspeert;N. Kubota
中科院分区：
文献类型：
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作者：
Azhar Aulia Saputra;A. Ijspeert;N. Kubota
在四足动物运动领域，动态运动行为和与感觉反馈的丰富整合代表了一个重要的发展。在本文中，我们提出了一个有效的神经模型，其中包括CPG和它的感觉运动协调，并展示了它的实施在四足机器人，以显示如何有效地整合电机和感觉反馈可以产生动态行为和感觉运动协调重建的感觉网络腿故障补偿。此外，我们描绘了一个网络优化策略，并建议感觉运动协调作为控制速度和调节内部和外部适应的策略。代表腿部损伤的节律产生是不活跃的，在没有任何命令参数的情况下刺激感觉运动系统重建CPG和足部力传入之间的网络。仿真和真实的猫型机器人在平坦和粗糙地形上的性能以及腿部故障测试表明了该模型的有效性，表明在腿部突然故障时可以产生平滑的步态模式过渡。
In the field of quadruped locomotion, dynamic locomotion behavior, and rich integration with sensory feedback represents a significant development. In this paper, we present an efficient neural model, which includes CPG and its sensorimotor coordination, and demonstrate its implementation in a quadruped robot to show how efficient integration of motor and sensory feedback can generate dynamic behavior and how sensorimotor coordination reconstructs the sensory network for leg malfunction compensation. Additionally, we delineate a network optimization strategy and suggest sensorimotor coordination as a strategy for controlling speed and regulating internal and external adaptation. The rhythm generation representing the leg injury was inactive, stimulating the sensorimotor system to reconstruct the network between CPG and feet force afferent without any commanding parameter. The performances of the simulated and real, cat-like robot on both flat and rough terrains and the leg malfunction tests demonstrated the effectiveness of the proposed model, indicating that a smooth gait-pattern transition could be generated during sudden leg malfunction.