QP-Based Visual Servoing Under Motion Blur-Free Constraint
This letter proposes a QP-based visual servoing scheme for limiting motion blur during the achievement of a visual task. Unlike traditional image restoration approaches, we want to avoid any deconvolution step by keeping the image sequence acquired by the camera as sharp as possible. To do so, we select the norm of the image gradient as sharpness metric, from which we design a velocity constraint that is injected in a QP controller. Our system is evaluated for an Earth observation satellite. Simulation and experimental results show the effectiveness of our approach.
Authors
- Éric Marchand (ORCID: https://orcid.org/0000-0001-7096-5236)
- R. Fraïssé (ORCID: https://orcid.org/0009-0005-4159-4276)
- François Chaumette (ORCID: https://orcid.org/0000-0002-1238-4385)
- Maxime Robic (ORCID: https://orcid.org/0009-0008-8393-869X)
Institutions
- Airbus (France) (FR)
- Centre National de la Recherche Scientifique (FR)
- Institut national de recherche en sciences et technologies du numérique (FR)
- Institut de Recherche en Informatique et Systèmes Aléatoires (FR)
- Université de Rennes (FR)
Publication Details
- Journal
- IEEE Robotics and Automation Letters
- Published
- 2024-08-29
- DOI
- https://doi.org/10.1109/lra.2024.3451394
- Citations
- 2
- Primary Topic
- Advanced Vision and Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.50