Fast Online Planning for Bipedal Locomotion via Centroidal Model Predictive Gait Synthesis
نویسندگان
چکیده
The planning of whole-body motion and step time for bipedal locomotion is constructed as a model predictive control (MPC) problem, in which sequence optimization problems needs to be solved online. While directly solving these extremely time-consuming, we propose gait synthesizer offer immediate solutions. Based on the full-dimensional model, library gaits with different speeds periods first offline. Then proposed generates real-time at 1 kHz by synthesizing based online prediction centroidal dynamics. We prove that MPC problem can ensure uniform ultimate boundedness (UUB) CoM states show our provide feasible solutions problems. Simulation experimental results robot 8 degrees freedom (DoF) are provided performance robustness this approach.
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ژورنال
عنوان ژورنال: IEEE robotics and automation letters
سال: 2021
ISSN: ['2377-3766']
DOI: https://doi.org/10.1109/lra.2021.3092268