Keywords:
- active learning
- assistive robotics
- Bayesian Gaussian mixture model
- Bayesian optimization
- differential kinematics
- domain knowledge
- Gaussian Mixture Model
- Gaussian mixture regression
- Gaussian process
- Gaussian processes
- generalized linear model
- learning from demonstration
- Learning from demonstrations
- manipulability ellipsoids
- mixture of experts
- multimodal regression
- programming by demonstration
- prosthetic hands
- regression
- Riemannian geometry
- Riemannian manifolds
- robot learning
- sEMG
- surface electromyography
- TACT-HAND project
- tactile myography
- tensor methods
Publications of N. Jaquier sorted by journal and type
International Journal of Robotic Research
| Geometry-aware Manipulability Learning, Tracking and Transfer, , , and , in: International Journal of Robotic Research, 40(2-3):624-650, 2021 |
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Micro & Nano Magazine, Micronarc
| Improving the control of prosthetic hands with tactile sensing, and , in: Micro & Nano Magazine, Micronarc:42-43, 2018 |
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Robotics and Autonomous Systems
| Tensor-variate mixture of experts for proportional myographic control of a robotic hand, , and , in: Robotics and Autonomous Systems, 142:103812, 2021 |
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Technologies
| Combining Electromyography and Tactile Myography to Improve Hand and Wrist Activity Detection in Prostheses, , , and , in: Technologies, 5(4), 2017 |
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Proc. IEEE/RSJ Intl Conf. on Intelligent Robots and Systems (2020)
| Active Improvement of Control Policies with Bayesian Gaussian Mixture Model, , , and , in: Proc. IEEE/RSJ Intl Conf. on Intelligent Robots and Systems, 2020 |
| Analysis and Transfer of Human Movement Manipulability in Industry-like Activities, , and , in: Proc. IEEE/RSJ Intl Conf. on Intelligent Robots and Systems, 2020 |
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Conference on Robot Learning (2019)
| Bayesian Optimization Meets Riemannian Manifolds in Robot Learning, , , and , in: Conference on Robot Learning, 2019 |
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| Learning from demonstration with model-based Gaussian process, , and , in: Conference on Robot Learning, 2019 |
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R:SS Pioneers Workshop (2018)
| Geometry-aware Control and Learning in Robotics, and , in: R:SS Pioneers Workshop, 2018 |
R:SS Workshop on Learning and Inference in Robotics: Integrating Structure, Priors and Models (2018)
| Geometry-aware Robot Manipulability Transfer, , and , in: R:SS Workshop on Learning and Inference in Robotics: Integrating Structure, Priors and Models, 2018 |
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Robotics: Science and Systems (2018)
| Geometry-aware Tracking of Manipulability Ellipsoids, , , and , in: Robotics: Science and Systems, Pittsburgh, USA, 2018 |
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Proc. IEEE/RSJ Intl Conf. on Intelligent Robots and Systems (2017)
| Gaussian Mixture Regression on Symmetric Positive Definite Matrices Manifolds: Application to Wrist Motion Estimation with sEMG, and , in: Proc. IEEE/RSJ Intl Conf. on Intelligent Robots and Systems, pages 59-64, 2017 |
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Proc. of the Myoelectric Control Symposium (2017)
| Improving hand and wrist activity detection using tactile sensors and tensor regression methods on Riemannian manifolds, , and , in: Proc. of the Myoelectric Control Symposium, 2017 |
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Proc. IEEE/RSJ Intl Conf. on Intelligent Robots and Systems (2017)
| Learning Manipulability Ellipsoids for Task Compatibility in Robot Manipulation, , , and , in: Proc. IEEE/RSJ Intl Conf. on Intelligent Robots and Systems, pages 3183-3189, 2017 |
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Publications of type Phdthesis
2020
| Robot skills learning with Riemannian manifolds : Leveraging geometry-awareness in robot learning, optimization and control, , Ecole Polytechnique Fédérale de Lausanne, 2020 |
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