Fangyu Shen, Yuanyuan Liu, Xiao Li, Qingying He, Chengming Tian, and Sun Hao
Bipedal robot, Bezier curve, trajectory planning, gait optimisation, biomechanical characteristic
As bipedal robot application scenarios expand, traditional planning methods face limitations in balancing efficiency and biomimetic characteristics. This paper proposes a bilayer B´ezier curve optimisation method for gait trajectory planning of bipedal robots on unstructured terrain. Unlike existing single-layer B´ezier curve and traditional polynomial interpolation methods, this approach innovatively designs a cooperative optimisation architecture for motion state layer and swing phase space layer, achieving an organic integration of macro-level trajectory continuity and micro- level biomechanical characteristics. Through adaptive selection of B´ezier curve order and foot trajectory optimisation based on human biomechanical features, the method achieves optimal balance between computational efficiency and trajectory smoothness while realising natural gait patterns. Experimental results show excellent performance across three typical testing scenarios: response time reduced by approximately 50% on ideal level pavement; mean square error decreased by 94.9% compared to traditional methods on cosine wave pavement; and in random rough pavement, center of mass stability improved by 44.1% with mean square error reduced by 74.4%.
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