A Framework for Robust and Incremental Self-Localization of a Mobile Robot

In this contribution we present a framework for an embodied robotic system that is capable of appearance-based self-localization. Specifically, we concentrate on the issues of robustness, flexibility, and scalability of the system. The framework presented is based on a panoramic eigenspace model of the environment. Its main feature is that it allows for simultaneous localization and map building using an incremental learning algorithm. Further, both the learning and the training processes are designed in a way to achieve robustness and adaptability to changes in the environment.

[1]  Kostas Daniilidis,et al.  Catadioptric Projective Geometry , 2001, International Journal of Computer Vision.

[2]  Horst Bischof,et al.  Mobile robot localization under varying illumination , 2002, Object recognition supported by user interaction for service robots.

[3]  A. Leonardis,et al.  Robust localization using eigenspace of spinning-images , 2000, Proceedings IEEE Workshop on Omnidirectional Vision (Cat. No.PR00704).

[4]  Horst Bischof,et al.  Robust Recognition Using Eigenimages , 2000, Comput. Vis. Image Underst..

[5]  Hiroshi Murase,et al.  Detection of 3D objects in cluttered scenes using hierarchical eigenspace , 1997, Pattern Recognit. Lett..

[6]  Ralph R. Martin,et al.  Incremental Eigenanalysis for Classification , 1998, BMVC.

[7]  Horst Bischof,et al.  Multiple eigenspaces , 2002, Pattern Recognit..

[8]  Hiroshi Murase,et al.  Subspace methods for robot vision , 1996, IEEE Trans. Robotics Autom..

[9]  S. Nayar,et al.  Early Visual Learning , 1996 .

[10]  José Santos-Victor,et al.  Vision-based navigation and environmental representations with an omnidirectional camera , 2000, IEEE Trans. Robotics Autom..

[11]  P. Hall,et al.  Series No : 98001 Incremental Eigenanalysis for Classification , 1998 .

[12]  Ales Leonardis,et al.  Robust localization using an omnidirectional appearance-based subspace model of environment , 2003, Robotics Auton. Syst..

[13]  Rolf Pfeifer,et al.  Understanding intelligence , 2020, Inequality by Design.

[14]  Horst Bischof,et al.  A Robust PCA Algorithm for Building Representations from Panoramic Images , 2002, ECCV.

[15]  Sam T. Roweis,et al.  EM Algorithms for PCA and SPCA , 1997, NIPS.

[16]  Hiroshi Murase,et al.  Illumination Planning for Object Recognition Using Parametric Eigenspaces , 1994, IEEE Trans. Pattern Anal. Mach. Intell..

[17]  Ales Leonardis,et al.  Robust localization using panoramic view-based recognition , 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.

[18]  Alex Pentland,et al.  Face recognition using eigenfaces , 1991, Proceedings. 1991 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[19]  Nobuyuki Kita,et al.  Sequential localisation and map-building for real-time computer vision and robotics , 2001, Robotics Auton. Syst..

[20]  Ales Leonardis,et al.  Mobile robot localization using an incremental eigenspace model , 2002, Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292).