Comparison Study of Nonlinear Optimization of Step Durations and Foot Placement for Dynamic Walking
This work addresses robustness in dynamic walking for bipedal robots, presenting an incremental improvement in computational efficiency.
The paper tackled the problem of robust bipedal walking by optimizing step durations and foot placement using nonlinear optimization, finding that a sequential approach achieved similar optimal solutions as a holistic method but with significantly reduced computational time, making it suitable for real-time implementation.
This paper studies bipedal locomotion as a nonlinear optimization problem based on continuous and discrete dynamics, by simultaneously optimizing the remaining step duration, the next step duration and the foot location to achieve robustness. The linear inverted pendulum as the motion model captures the center of mass dynamics and its low-dimensionality makes the problem more tractable. We first formulate a holistic approach to search for optimality in the three-dimensional parametric space and use these results as baseline. To further improve computational efficiency, our study investigates a sequential approach with two stages of customized optimization that first optimizes the current step duration, and subsequently the duration and location of the next step. The effectiveness of both approaches is successfully demonstrated in simulation by applying different perturbations. The comparison study shows that these two approaches find mostly the same optimal solutions, but the latter requires considerably less computational time, which suggests that the proposed sequential approach is well suited for real-time implementation with a minor trade-off in optimality.