Intelligent stereo vision in autonomous robot traversability estimation
2012 (English)In: Robotic Vision: Technologies for Machine Learning and Vision Applications, IGI Global, 2012, 193-209 p.Chapter in book (Refereed)
Traversability estimation is the process of assessing whether a robot is able to move across a specific area. Autonomous robots need to have such an ability to automatically detect and avoid non-traversable areas and, thus, stereo vision is commonly used towards this end constituting a reliable solution under a variety of circumstances. This chapter discusses two different intelligent approaches to assess the traversability of the terrain in front of a stereo vision-equipped robot. First, an approach based on a fuzzy inference system is examined and then another approach is considered, which extracts geometrical descriptions of the scene depth distribution and uses a trained support vector machine (SVM) to assess the traversability. The two methods are presented and discussed in detail.
Place, publisher, year, edition, pages
IGI Global, 2012. 193-209 p.
IdentifiersURN: urn:nbn:se:kth:diva-162991DOI: 10.4018/978-1-4666-2672-0.ch012ScopusID: 2-s2.0-84900668068ISBN: 978-146662672-0OAI: oai:DiVA.org:kth-162991DiVA: diva2:798779
QC 201503272015-03-272015-03-262015-03-27Bibliographically approved