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Intelligent robots need intelligent vision: Visual 3D perception
Royal Military Academy, Belgium.
Production and Management Engineering Dept., Democritus University of Thrace, Greece.
Electrical and Computer Engineering Dept., Democritus University of Thrace, Greece.
Production and Management Engineering Dept., Democritus University of Thrace, Greece.
2008 (English)Conference paper (Refereed)
Abstract [en]

Contemporary autonomous robots are generally equipped with an abundance of sensors like for example GPS, Laser, ultrasound sensors, etc to be able to navigate in an environment. However, this stands in contrast to the ultimate biological example for these robots: us humans. Indeed, humans seem perfectly capable to navigate in a complex, dynamic environment using primarily vision as a sensing modality. This observation inspired us to investigate visually guided intelligent mobile robots. In order to understand and reason about its environment, an intelligent robot needs to be aware of the three-dimensional status of this environment. The problem with vision, though, is that the perceived image is a two-dimensional projection of the 3D world. Recovering 3D-information has been in the focus of attention of the computer vision community for a few decades now, yet no all-satisfying method has been found so far. Most attention in this area has been on stereo-vision based methods, which use the displacement of objects in two (or more) images. Where stereo vision must be seen as a spatial integration of multiple viewpoints to recover depth, it is also possible to perform a temporal integration. The problem arising in this situation is known as the "Structure from Motion" (SfM) problem and deals with extracting 3-dimensional information about the environment from the motion of its projection onto a two-dimensional surface. In this paper, we investigate the possibilities of stereo and structure from motion approaches. It is not the aim to compare both theories of depth reconstruction with the goal of designating a winner and a loser. Both methods are capable of providing sparse as well as dense 3D reconstructions and both approaches have their merits and defects. The thorough, year-long research in the field indicates that accurate depth perception requires a combination of methods rather than a sole one. In fact, cognitive research has shown that the human brain uses no less than 12 different cues to estimate depth. Therefore, we also finally introduce in a following section a methodology to integrate stereo and structure from motion.

Place, publisher, year, edition, pages
National Category
Computer Vision and Robotics (Autonomous Systems)
URN: urn:nbn:se:kth:diva-51023OAI: diva2:463244
IARP/EURON Workshop on Robotics for Risky Interventions and Environmental Surveillance. Benicassim, Spain. January 7th-8th, 2008
Vision and Chemiresistor Equipped Web-connected Finding Robots (View-Finder), FP6-IST-2006-045541
QC 20111214Available from: 2011-12-08 Created: 2011-12-08 Last updated: 2011-12-14Bibliographically approved

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Nalpantidis, Lazaros
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