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Proposal of Methodology of a Bipedal Humanoid Gait Generation Based on Cognitive Algorithm

Part of the Lecture Notes in Computer Science book series (LNIP,volume 11379)


This article proposes a methodology of generating a bipedal humanoid gait pattern for the knee and hip leg joints in the sagittal plane. The multi-functional gait movement is divided into three different movement patterns with a specific function, which can be modulated individually and superposed to compose a gait pattern. This strategy is based on the potential field navigation algorithm concept (proposed by Khatib, 1986) and the architecture for its application is based the AuRA cognitive architecture (proposed by Arkin, 1990). Finally, this methodology was validated using a MATLAB-SimulinkTM implementation of a simplified kinematic model of the legs movements. The results show movement patterns close to the biomechanical ones at the joints. When applied to the kinematic model, those joint movements generate feet trajectories that are compatible to the gait both in shape and amplitude. The strategy was also embedded in a microcontroller prototype, revealing low computational demands as well as another view for the generated movement.

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Correspondence to João Maurício Rosário .

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Rosário, J.M., Suekichi Kuteken, R., Izquierdo Cordoba, L.M. (2019). Proposal of Methodology of a Bipedal Humanoid Gait Generation Based on Cognitive Algorithm. In: Lepore, N., Brieva, J., Romero, E., Racoceanu, D., Joskowicz, L. (eds) Processing and Analysis of Biomedical Information. SaMBa 2018. Lecture Notes in Computer Science(), vol 11379. Springer, Cham.

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  • Print ISBN: 978-3-030-13834-9

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