/paper_viceconte_2021_ral_adherent

Primary LanguagePythonBSD 3-Clause "New" or "Revised" LicenseBSD-3-Clause

ADHERENT: Learning Human-like Trajectory Generators for Whole-body Control of Humanoid Robots

P. M. Viceconte, R. Camoriano, G. Romualdi, D. Ferigo, S. Dafarra, S. Traversaro, G. Oriolo, L. Rosasco and D. Pucci, "ADHERENT: Learning Human-like Trajectory Generators for Whole-body Control of Humanoid Robots" in IEEE Robotics and Automation Letters, vol. 7, no. 2, pp. 2779-2886, April 2022, doi: 10.1109/LRA.2022.3141658

ADHERENT.Learning.Human-like.Trajectory.Generators.for.Whole-body.Control.of.Humanoid.Robots.mp4

IEEE Robotics and Automation Letters
Installation | Paper | Video

Installation

In order to reproduce the results related to this work, please configure your setup by following the ADHERENT setup configuration wiki and then follow one or more sections from the ADHERENT scripts execution wiki.

Citing this work

If you find the work useful, please consider citing:

@ARTICLE{9676410,
  author={Viceconte, Paolo Maria and Camoriano, Raffaello and Romualdi, Giulio and Ferigo, Diego and Dafarra, Stefano and Traversaro, Silvio and Oriolo, Giuseppe and Rosasco, Lorenzo and Pucci, Daniele},
  journal={IEEE Robotics and Automation Letters},
  title={ADHERENT: Learning Human-like Trajectory Generators for Whole-body Control of Humanoid Robots},
  year={2022},
  volume={7},
  number={2},
  pages={2779-2886},
  doi={10.1109/LRA.2022.3141658}}

Maintainer

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@paolo-viceconte