Rapid and Robust Trajectory Optimization for Humanoids

Fuente: arXiv
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Autores principales: Zhang, Bohao, Vasudevan, Ram
Formato: Preprint
Publicado: 2024
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author Zhang, Bohao
Vasudevan, Ram
author_facet Zhang, Bohao
Vasudevan, Ram
contents 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/.
format Preprint
id arxiv_https___arxiv_org_abs_2409_00303
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Rapid and Robust Trajectory Optimization for Humanoids
Zhang, Bohao
Vasudevan, Ram
Robotics
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/.
title Rapid and Robust Trajectory Optimization for Humanoids
topic Robotics
url https://arxiv.org/abs/2409.00303