Aniket Murarka, Joseph Modayil, and Benjamin Kuipers. 2006.
safety maps for a wheelchair robot using vision and
Canadian Conference on Computer and Robot Vision
- Best Student Paper Award at CRV-06!
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 range-finders 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.