IROS 2015 Paper Abstract


Paper ThDT3.3

Crombez, Nathan (Université de Picardie Jules Verne - Laboratoire MIS), Caron, Guillaume (Université de Picardie Jules Verne), Mouaddib, El Mustapha (Université of Picardie Jules Verne)

Photometric Gaussian Mixtures Based Visual Servoing

Scheduled for presentation during the Regular session "Visual Servoing" (ThDT3), Thursday, October 1, 2015, 14:30−14:45, Saal E

2015 IEEE/RSJ International Conference on Intelligent Robots and Systems, Sept 28 - Oct 03, 2015, Congress Center Hamburg, Hamburg, Germany

This information is tentative and subject to change. Compiled on July 19, 2019

Keywords Visual Servoing


The advantages of using the entire photometric image information as visual feature are: it does not require any feature detections, matching or tracking process. To enlarge the convergence domain, we propose to accomplish visual servoing based on the analytical formulation of Gaussian mixtures to model the images. During the servoing, we consider the optimization of the Gaussian spreads allowing the camera to converge to a desired pose even from a far initial one. Simulation that overcomes the state-of-the-art and real experiments highlight the success of our approach.



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