Visual Based Navigation of Mobile Robots
This work addresses indoor navigation for personal assistant robots, but it appears incremental as it builds on existing methods like SLIC and occupancy grids.
The paper tackles the problem of enabling mobile robots to navigate indoors using only monocular vision, resulting in a mapping technique that is robust and supports very fast updates.
We have developed an algorithm to generate a complete map of the traversable region for a personal assistant robot using monocular vision only. Using multiple taken by a simple webcam, obstacle detection and avoidance algorithms have been developed. Simple Linear Iterative Clustering (SLIC) has been used for segmentation to reduce the memory and computation cost. A simple mapping technique using inverse perspective mapping and occupancy grids, which is robust, and supports very fast updates has been used to create the map for indoor navigation.