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Author Cauchois, Cyril ♦ Brassart, Eric ♦ Marhic, Bruno ♦ Drocourt, Cyril
Source CiteSeerX
Content type Text
File Format PDF
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Brief Outline ♦ Calibration Process ♦ Vision Sensor ♦ Radial Segment ♦ Omnidirectional Image Formation Process ♦ Real Noisy Omnidirectional Image ♦ Main Motivation ♦ Artificial Indoor Environment ♦ Vertical Environment Landmark Projection ♦ Conical Vision Sensor ♦ Syclop Sensor ♦ Syclop Geometry ♦ Conical Omnidirectional Vision Sensor ♦ Synthetic Image Base ♦ Radial Straight Line ♦ Absolute Mobile Robot Self-localization Algorithm ♦ Goniometric One ♦ Experimental Result ♦ Synthetic Panoramic Image Base ♦ Localization Method ♦ Absolute Localization Method
Description Proc. IEEE Workshop on Omnidirectional Vision
This paper deals with an absolute mobile robot self-localization algorithm in an artificial indoor environment. Until now, localization methods based on conical omnidirectional vision sensors uniquely used radial segments from vertical environment landmarks projection. The main motivation of this work is to show that primitives other than radial straight lines are usable with a conical vision sensor. In other words, the goal of this paper is to demonstrate that the SYCLOP sensor can be used as a vision sensor rather than a goniometric one. After a brief outline of SYCLOP geometry and the calibration process, we will show how the calibration allows us to know the omnidirectional image formation process to compute a synthetic image base. Then, we will present the localization method. Finally, some experimental results obtained with real noisy omnidirectional images acquired in an artificial indoor environment are shown.
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study
Learning Resource Type Article