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Goto, Tatsumi; Okamoto, Rina; Ishihama, Takumi; Yamazaki, Kentaro; Kokubun, Yugo; Kaneko, Minami; Uchikoba, Fumio
Artificial life and robotics, 05/2024, Letnik: 29, Številka: 2Journal Article
Most conventional biped robots process leg movements and information from each sensor by numerical calculation using a CPU. However, to cope with diverse environments, the numerical calculations are enormous, so they must be processed at high speed using a high-performance CPU and high power consumption. On the other hand, focusing on human motor control, it is believed that basic motor patterns such as walking and running are generated by a neural network called the central pattern generator (CPG), which is localized in the spinal cord and is independent of calculation. We previously focused on pulse-type hardware neural networks (P-HNNs), in which the neural network was composed of analog electronic circuits, and developed a hardware CPG model for controlling a single leg of a musculoskeletal humanoid robot. However, to actually move a biped robot, a CPG model that takes into account both legs and sensory information is required. Therefore, this study aims to develop a hardware CPG model for controlling both legs of a musculoskeletal humanoid robot whose gait changes according to the higher center and sensory information. We report on a hardware CPG model configured by circuit simulation confirmed the generation of walking and running patterns.
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JCR | SNIP | JCR | SNIP | JCR | SNIP | JCR | SNIP |
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