Dynamical System-based Imitation Learning for Visual Servoing using the Large Projection Formulation - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Conference Papers Year : 2023

Dynamical System-based Imitation Learning for Visual Servoing using the Large Projection Formulation

Abstract

Nowadays ubiquitous robots must be adaptive and easy to use. To this end, dynamical system-based imitation learning plays an important role. In fact, it allows to realize stable and complex robotic tasks without explicitly coding them, thus facilitating the robot use. However, the adaptation capabilities of dynamical systems have not been fully exploited due to the lack of closed-loop implementations making use of visual feedback. In this regard, the integration of visual information allows higher flexibility to cope with environmental changes. This work presents a dynamical system-based imitation learning for visual servoing, based on the large projection task priority formulation. The proposed scheme enables complex and stable visual tasks, as demonstrated by a simulation analysis and experiments with a robotic manipulator.

Domains

Automatic
Fichier principal
Vignette du fichier
ICRA23_1381_FI.pdf (3.35 Mo) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-04019727 , version 1 (08-03-2023)

Identifiers

  • HAL Id : hal-04019727 , version 1

Cite

Antonio Paolillo, Paolo Robuffo Giordano, Matteo Saveriano. Dynamical System-based Imitation Learning for Visual Servoing using the Large Projection Formulation. ICRA 2023 - IEEE International Conference on Robotics and Automation, May 2023, London, United Kingdom. pp.1-7. ⟨hal-04019727⟩
71 View
355 Download

Share

Gmail Facebook X LinkedIn More