3D Perception and Environment Map Generation for Humanoid Robot Navigation
- 1 October 2008
- journal article
- research article
- Published by SAGE Publications in The International Journal of Robotics Research
- Vol. 27 (10), 1117-1134
- https://doi.org/10.1177/0278364908096316
Abstract
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.Keywords
This publication has 5 references indexed in Scilit:
- Generalized principal component analysis (GPCA)IEEE Transactions on Pattern Analysis and Machine Intelligence, 2005
- A Real-Time Expectation-Maximization Algorithm for Acquiring Multiplanar Maps of Indoor Environments With Mobile RobotsIEEE Transactions on Robotics and Automation, 2004
- Learning compact 3D models of indoor and outdoor environments with a mobile robotRobotics and Autonomous Systems, 2003
- An experimental comparison of range image segmentation algorithmsIEEE Transactions on Pattern Analysis and Machine Intelligence, 1996
- Fast segmentation of range images into planar regions by scan line groupingMachine Vision and Applications, 1994