Leonel Rozo
Leonel Rozo coauthored Learning Riemannian Manifolds for Geodesic Motion Skills. The team learned robot movement patterns from human demonstrations using a variational autoencoder. It represented those patterns as a Riemannian manifold, where geodesic paths become motion skills. Experiments with a seven-degree-of-freedom manipulator tested reproduction of demonstrated movements, adaptation to unseen obstacles and generation of new movements. Leonel Rozo and the Learning Riemannian Manifolds for Geodesic Motion Skills team received the RSS 2021 Best Student Paper Award.
- Works
- 65
- Citations
- 1,991
- h-index
- 21
Publication numbers from OpenAlex, as of 14 October 2026.
Timeline
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2021
A shared Learning Riemannian Manifolds for Geodesic Motion Skills contribution
Leonel Rozo coauthored Learning Riemannian Manifolds for Geodesic Motion Skills. The team learned robot movement patterns from human demonstrations using a variational autoencoder. It represented those patterns as a Riemannian manifold, where geodesic paths become motion skills. Experiments with a seven-degree-of-freedom manipulator tested reproduction of demonstrated movements, adaptation to unseen obstacles and generation of new movements.
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2021
Conference recognition
Leonel Rozo and the Learning Riemannian Manifolds for Geodesic Motion Skills team received the RSS 2021 Best Student Paper Award.
Sources and credits
Photo: leonelrozo.weebly.com; Leonel Rozo - Home; creator not stated. License: Not stated by source. Source: leonelrozo.weebly.com. Cropped to a square and resized. Ask us to remove or replace this photo.