Abstract
This paper presents a novel approach for incremental semiparametric inverse dynamics learning. In particular, we consider the mixture of two approaches: Parametric modeling based on rigid body dynamics equations and nonparametric modeling based on incremental kernel methods, with no prior information on the mechanical properties of the system. The result is an incremental semiparametric approach, leveraging the advantages of both the parametric and nonparametric models. We validate the proposed technique learning the dynamics of one arm of the iCub humanoid robot.
DOI
10.1109/icra.2016.7487177
Publication Date
2016-05-01
Event
2016 IEEE International Conference on Robotics and Automation (ICRA)
Publication Title
2016 IEEE International Conference on Robotics and Automation (ICRA)
Publisher
IEEE
Embargo Period
2024-11-22
Recommended Citation
Camoriano, R., Traversaro, S., Rosasco, L., Metta, G., & Nori, F. (2016) 'Incremental semiparametric inverse dynamics learning', 2016 IEEE International Conference on Robotics and Automation (ICRA), . IEEE: Available at: https://doi.org/10.1109/icra.2016.7487177
