The intended application of this research is to integrate stereo vision and SLAM to create a map while a robotic wheelchair is navigating in its environment. The vision based mapping is one component of the assisted navigation system being developed for the wheelchair.
Simultaneous localization and mapping (SLAM) has been widely used for navigation and typically makes use of laser range-finders or sonar. We are going to use pmap, a SLAM implementation that assumes the use of a SICK laser. It will be modified to accommodate the stereo vision data.
An advantage of using stereo vision over laser range-finders is the ability to detect obstacles at different heights. Laser range-finders return distance measurements on a 2D plane at a fix height. With stereo vision we can mark the closest obstacle regardless of height. For example, when a laser range finder sees four table legs, it only marks the table legs as occupied space in the map. This could cause a robot to try to drive under a table it should be avoiding. Our stereo vision approach would be able to detect the entire table and avoid collision.
Maps generated using stereovision and PMAP.