Year: 2024
Type: conference-paper
Abstract: This paper presents a novel approach for Visual Servoing (VS) using a multispectral camera, where the number of data are more than three times that of a standard color camera. To meet real-time feasibility, the multispectral data captured by the camera are processed using dimensionality reduction techniques. Instead of relying on traditional approaches that select a subset of bands, the proposed method unlocks the full potential of a multispectral camera by pinpointing individual pixels that hold the richest information across all bands. While sacrificing spectral resolution for enhanced spatial resolution - crucial for precise robotic control in forested environments - this fusion process offers a powerful tool for robust and real-time VS in natural settings. Validated through simulations and real-world experiments, the proposed approach demonstrates its efficacy by leveraging the full spectral information of the camera while preserving spatial details.
Authors: Enrico Fiasché, Ezio Malis, Philippe Martinet
Institutions: Université Côte d'Azur, Centre Inria d'Université Côte d'Azur
Language: English
Topic: Advanced Vision and Imaging
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
Funder: Agence Nationale de la Recherche
OpenAlex ID: W4402548732