Complementarity-Free Multi-Contact Modeling and Optimization for Dexterous Manipulation

Fuente: arXiv
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Main Author: Jin, Wanxin
Format: Preprint
Published: 2024
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author Jin, Wanxin
author_facet Jin, Wanxin
contents A significant barrier preventing model-based methods from achieving real-time and versatile dexterous robotic manipulation is the inherent complexity of multi-contact dynamics. Traditionally formulated as complementarity models, multi-contact dynamics introduces non-smoothness and combinatorial complexity, complicating contact-rich planning and optimization. In this paper, we circumvent these challenges by introducing a lightweight yet capable multi-contact model. Our new model, derived from the duality of optimization-based contact models, dispenses with the complementarity constructs entirely, providing computational advantages such as closed-form time stepping, differentiability, automatic satisfaction with Coulomb friction law, and minimal hyperparameter tuning. We demonstrate the effectiveness and efficiency of the model for planning and control in a range of challenging dexterous manipulation tasks, including fingertip 3D in-air manipulation, TriFinger in-hand manipulation, and Allegro hand on-palm reorientation, all performed with diverse objects. Our method consistently achieves state-of-the-art results: (I) a 96.5% average success rate across all objects and tasks, (II) high manipulation accuracy with an average reorientation error of 11° and position error of 7.8mm, and (III) contact-implicit model predictive control running at 50-100 Hz for all objects and tasks. These results are achieved with minimal hyperparameter tuning.
format Preprint
id arxiv_https___arxiv_org_abs_2408_07855
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Complementarity-Free Multi-Contact Modeling and Optimization for Dexterous Manipulation
Jin, Wanxin
Robotics
A significant barrier preventing model-based methods from achieving real-time and versatile dexterous robotic manipulation is the inherent complexity of multi-contact dynamics. Traditionally formulated as complementarity models, multi-contact dynamics introduces non-smoothness and combinatorial complexity, complicating contact-rich planning and optimization. In this paper, we circumvent these challenges by introducing a lightweight yet capable multi-contact model. Our new model, derived from the duality of optimization-based contact models, dispenses with the complementarity constructs entirely, providing computational advantages such as closed-form time stepping, differentiability, automatic satisfaction with Coulomb friction law, and minimal hyperparameter tuning. We demonstrate the effectiveness and efficiency of the model for planning and control in a range of challenging dexterous manipulation tasks, including fingertip 3D in-air manipulation, TriFinger in-hand manipulation, and Allegro hand on-palm reorientation, all performed with diverse objects. Our method consistently achieves state-of-the-art results: (I) a 96.5% average success rate across all objects and tasks, (II) high manipulation accuracy with an average reorientation error of 11° and position error of 7.8mm, and (III) contact-implicit model predictive control running at 50-100 Hz for all objects and tasks. These results are achieved with minimal hyperparameter tuning.
title Complementarity-Free Multi-Contact Modeling and Optimization for Dexterous Manipulation
topic Robotics
url https://arxiv.org/abs/2408.07855