Performing trajectory design for humanoid robots with high degrees of freedom is computationally challenging. The trajectory design process also often involves carefully selecting various hyperparameters and requires a good initial guess which can further complicate the development process. This work introduces a generalized gait optimization framework that directly generates smooth and physically feasible trajectories. The proposed method demonstrates faster and more robust convergence than existing techniques and explicitly incorporates closed-loop kinematic constraints that appear in many modern humanoids. The method is implemented as an open-source C++ codebase which can be found at https://roahmlab.github.io/RAPTOR/.
@article{arxiv.2409.00303,
title = {Rapid and Robust Trajectory Optimization for Humanoids},
author = {Bohao Zhang and Ram Vasudevan},
journal= {arXiv preprint arXiv:2409.00303},
year = {2024}
}