An Experimental System for Incremental Environment Modelling by an Autonomous Mobile Robot
The First International Symposium on Experimental Robotics I
FastSLAM: a factored solution to the simultaneous localization and mapping problem
Eighteenth national conference on Artificial intelligence
CRV '06 Proceedings of the The 3rd Canadian Conference on Computer and Robot Vision
Real-time Localization in Outdoor Environments using Stereo Vision and Inexpensive GPS
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 03
MonoSLAM: Real-Time Single Camera SLAM
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Study of the Rao-Blackwellised Particle Filter for Efficient and Accurate Vision-Based SLAM
International Journal of Computer Vision
Detailed Real-Time Urban 3D Reconstruction from Video
International Journal of Computer Vision
Stereo vision specific models for particle filter-based SLAM
Robotics and Autonomous Systems
Leaving flatland: toward real-time 3D navigation
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
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This paper deals with the path-planning of a robot during the exploration and 3D map building in the unknown environment. The robot uses a stereocamera for significant features detection, then matches them in both images and computes their 3D coordinates. This way the robot incrementally creates the 3D map of its surroundings and tries to explore as much area as possible. This paper describes the way of marking the traversable path in the map created so far and the path planning to the next explored goal point. As the map uses points and triangles to represent shape of the surface, the traversable area marking and the path planning is also done in the map which is represented in the same way.