Factoring the Mapping Problem: Mobile Robot Map-building in the Hybrid Spatial Semantic Hierarchy
International Journal of Robotics Research
Proceedings of the 4th ACM International Workshop on Context-Awareness for Self-Managing Systems
CC-RANSAC: Fitting planes in the presence of multiple surfaces in range data
Pattern Recognition Letters
Stereovision-based obstacle avoidance procedure for autonomous mobile platforms
HAIS'11 Proceedings of the 6th international conference on Hybrid artificial intelligent systems - Volume Part I
Disparity map based procedure for collision-free guidance through unknown environments
ICCVG'12 Proceedings of the 2012 international conference on Computer Vision and Graphics
A development and evaluation platform for non-tactile power wheelchair controls
Proceedings of the 6th International Conference on PErvasive Technologies Related to Assistive Environments
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To be useful as a mobility assistant for a human driver, an intelligent robotic wheelchair must be able to distinguish between safe and hazardous regions in its immediate environment. We present a hybrid method using laser rangefinders and vision for building local 2D metrical maps that incorporate safety information (called local safety maps). Laser range-finders are used for localization and mapping of obstacles in the 2D laser plane, and vision is used for detection of hazards and other obstacles in 3D space. The hazards and obstacles identified by vision are projected into the travel plane of the robot and combined with the laser map to construct the local 2D safety map. The main contributions of this work are (i) the definition of a local 2D safety map, (ii) a hybrid method for building the safety map, and (iii) a method for removing noise from dense stereo data using motion.