# Learning Stable Dynamical Systems for Visual Servoing

arXiv: https://arxiv.org/abs/2204.05681 · HTML: https://mlsanity.com/paper/2204.05681/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Placed in Robot manipulation imitation learning, one of 13 directions in Offline RL and imitation learning from data.
- First posted on arXiv 12 Apr 2022.

## Placed in

- Offline RL and imitation learning from data / [Robot manipulation imitation learning](https://mlsanity.com/offlinerl/robot-manipulation-imitation-learning/)

## Built on by (most cited first, 3 of 3)

- [Fusion Dynamical Systems with Machine Learning in Imitation Learning: A Comprehensive Overview](https://mlsanity.com/paper/2403.19916/) (2024)
- [Imitation Learning-based Visual Servoing for Tracking Moving Objects](https://mlsanity.com/paper/2309.07729/) (2023)
- [Imitation Learning-based Direct Visual Servoing using the Large Projection Formulation](https://mlsanity.com/paper/2406.09120/) (2024)

## Abstract (arXiv)

This work presents the dual benefit of integrating imitation learning techniques, based on the dynamical systems formalism, with the visual servoing paradigm. On the one hand, dynamical systems allow to program additional skills without explicitly coding them in the visual servoing law, but leveraging few demonstrations of the full desired behavior. On the other, visual servoing allows to consider exteroception into the dynamical system architecture and be able to adapt to unexpected environment changes. The beneficial combination of the two concepts is proven by applying three existing dynamical systems methods to the visual servoing case. Simulations validate and compare the methods; experiments with a robot manipulator show the validity of the approach in a real-world scenario.