Fast segmentation of range images into planar regions by scan line grouping
Machine Vision and Applications
An Experimental Comparison of Range Image Segmentation Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape registration using optimization for mobile robot navigation
Shape registration using optimization for mobile robot navigation
Lack-of-fit Detection using the Run-distribution Test
ECCV '94 Proceedings of the Third European Conference-Volume II on Computer Vision - Volume II
Visually Realistic Mapping of a Planar Environment with Stereo
ISER '00 Experimental Robotics VII
Segmentation of range images into planar regions
NRC '97 Proceedings of the International Conference on Recent Advances in 3-D Digital Imaging and Modeling
Real-Time Simultaneous Localisation and Mapping with a Single Camera
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Fast Segmentation of Planar Surfaces in Range Images
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 2 - Volume 2
Patchlets: a method of interpreting correlation stereo three-dimensional data
Patchlets: a method of interpreting correlation stereo three-dimensional data
Generalized Principal Component Analysis (GPCA)
IEEE Transactions on Pattern Analysis and Machine Intelligence
Using Extended EM to Segment Planar Structures in 3D
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 03
Real-time path planning for humanoid robot navigation
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Leaving flatland: toward real-time 3D navigation
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Following directions using statistical machine translation
Proceedings of the 5th ACM/IEEE international conference on Human-robot interaction
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A humanoid robot that can go up and down stairs, crawl underneath obstacles or simply walk around requires reliable perceptual capabilities for obtaining accurate and useful information about its surroundings. In this work we present a system for generating three-dimensional (3D) environment maps from data taken by stereo vision. At the core is a method for precise segmentation of range data into planar segments based on the algorithm of scan-line grouping extended to cope with the noise dynamics of stereo vision. In off-line experiments we demonstrate that our extensions achieve a more precise segmentation. When compared to a previously developed patch-let method, we obtain a richer segmentation with a higher accuracy while also requiring far less computations. From the obtained segmentation we then build a 3D environment map using occupancy grid and floor height maps. The resulting representation classifies areas into one of six different types while also providing object height information. We apply our perception method for the navigation of the humanoid robot QRIO and present experiments of the robot stepping through narrow space, walking up and down stairs and crawling underneath a table.