Sajjad Manzoor, and Youngjin Choi
Central pattern generator (CPG), neural oscillator, integrate-and-fire neuron, hopping robot
In the paper, a novel algorithm for CPG (central pattern generator)-based jumping motion generation and its control is proposed for movement adjustment of a hopping robot on plain surface and staircases. The hopping robot is considered to be a two-mass inverted pendulum (TMIP) model composed of a rotary actuator to generate swing motion and a linear actuator to yield jumping motion. An energy-based neural oscillator is designed for motion control of the rotary actuator. While designing the neural oscillator, adaptability of the CPG is also considered by taking an angular compensation of the neural oscillator for earlier ground touch-down in case of staircases or uneven surface. Furthermore, the stability of the proposed neural oscillator is established in this paper. The jumping motion of the hopping robot is generated by the linear actuator, which is driven using a new integrate-and-fire neuron coupled to the neural oscillator of the rotary actuator. At the end, the effectiveness of the proposed algorithm is verified through simulations and their results are discussed.
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