tailieunhanh - Mobile Robots Navigation_1

Tham khảo sách 'mobile robots navigation_1', kỹ thuật - công nghệ, kĩ thuật viễn thông phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | 1 A 3D Omnidirectional Sensor For Mobile Robot Applications Rémi Boutteau Xavier Savatier Jean-Yves Ertaud and Bélahcène Mazari Institut de Recherche en Systèmes Electroniques Embarqués IRSEEM France 1. Introduction In most of the missions a mobile robot has to achieve - intervention in hostile environments preparation of military intervention mapping etc - two main tasks have to be completed navigation and 3D environment perception. Therefore vision based solutions have been widely used in autonomous robotics because they provide a large amount of information useful for detection tracking pattern recognition and scene understanding. Nevertheless the main limitations of this kind of system are the limited field of view and the loss of the depth perception. A 360-degree field of view offers many advantages for navigation such as easiest motion estimation using specific properties on optical flow Mouaddib 2005 and more robust feature extraction and tracking. The interest for omnidirectional vision has therefore been growing up significantly over the past few years and several methods are being explored to obtain a panoramic image rotating cameras Benosman Devars 1998 muti-camera systems and catadioptric sensors Baker Nayar 1999 . Catadioptric sensors . the combination of a camera and a mirror with revolution shape are nevertheless the only system that can provide a panoramic image instantaneously without moving parts and are thus well-adapted for mobile robot applications. The depth perception can be retrieved using a set of images taken from at least two different viewpoints either by moving the camera or by using several cameras at different positions. The use of the camera motion to recover the geometrical structure of the scene and the camera s positions is known as Structure From Motion SFM . Excellent results have been obtained during the last years with SFM approaches Pollefeys et al. 2004 Nister 2001 but with off-line algorithms that need to process all .