论文信息 - Appearance-based mapping and localisation using feature stability histograms

Appearance-based mapping and localisation using feature stability histograms

Proposed is an appearance-based mapping and localisation method based on the human memory model, which is used to build a feature stability histogram (FSH) at each node in the robot topological map. FSH registers local feature stability over time through a voting scheme, and most stable features are considered for mapping and Bayesian localisation. Experimental results are presented using omnidirectional images acquired through long-term acquisition considering: illumination changes, occlusions, random removal of features and perceptual aliasing. This method is able to adapt the internal node's representation through time to achieve global and local robot localisation.

[1] Radu Orghidan,et al. Catadioptric single-shot rangefinder for textured map building in robot navigation , 2007 .

[2] Luc Van Gool,et al. Omnidirectional Vision Based Topological Navigation , 2007, International Journal of Computer Vision.

[3] Matthijs C. Dorst. Distinctive Image Features from Scale-Invariant Keypoints , 2011 .

[4] Richard C. Atkinson,et al. Human Memory: A Proposed System and its Control Processes , 1968, Psychology of Learning and Motivation.

[5] Roland Siegwart,et al. A Robust Descriptor for Tracking Vertical Lines in Omnidirectional Images and Its Use in Mobile Robotics , 2009, Int. J. Robotics Res..

[6] Vivek A. Sujan,et al. Information based indoor environment robotic exploration and modeling using 2-D images and graphs , 2006, Auton. Robots.

[7] Sinisa Segvic,et al. A mapping and localization framework for scalable appearance-based navigation , 2009, Comput. Vis. Image Underst..

[8] Tom Duckett,et al. An adaptive appearance-based map for long-term topological localization of mobile robots , 2008, 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems.