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Gait Optimization for Legged Systems Through Mixed Distribution Cross-Entropy Optimization by Tsikelis, Ioannis; Chatzilygeroudis, Konstantinos is a scholarly article available to read on EtoBox.

What is Gait Optimization for Legged Systems Through Mixed Distribution Cross-Entropy Optimization about?

Legged robotic systems can play an important role in real-world applications due to their superior load-bearing capabilities, enhanced autonomy, and effective navigation on uneven terrain. They offer an optimal trade-off between mobility and payload capacity, excelling in diverse environments while maintaining efficiency in transporting heavy loads. However, planning and optimizing gaits and gait sequences for these robots presents significant challenges due to the complexity of their dynamic motion and the numerous optimization variables involved. Traditional trajectory optimization methods address these challenges by formulating the problem as an optimization task, aiming to minimize cost functions, and to automatically discover contact sequences. Despite their structured approach, optimization-based methods face substantial difficulties, particularly because such formulations result in highly nonlinear and difficult to solve problems. To address these limitations, we propose CrEGOpt, a bi-level optimization method that combines traditional trajectory optimization with a black-box optimization scheme. CrEGOpt at the higher level employs the Mixed Distribution Cross-Entropy Method

Author

Tsikelis, Ioannis; Chatzilygeroudis, Konstantinos

Published

2024

Language

EN