Omnidirectional sparse visual path following with occlusion-robust feature tracking

Omnidirectional vision sensors are very attractive for autonomous robots because they offer a rich source of environment information. The main challenge in using these for mobile robots is managing this wealth of information. A relatively recent approach is the use of fast wide baseline local features, which we developed and use in the novel sparse visual path following method described in this paper. These local features have the great advantage that they can be recognized even if the viewpoint differs significantly. This opens the door to a memory efficient description of a path by sparsely sampling it with images. We propose a method for reexecution of these paths by a series of visual homing operations. Motion estimation is done by simultaneously tracking the set of features, with recovery of lost features by backprojecting them from a local sparse 3D feature map. This yields a navigation method with unique properties: it is accurate, robust, fast, and without odometry error build-up.

[1]  Robert C. Bolles,et al.  Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography , 1981, CACM.

[2]  Richard I. Hartley,et al.  Estimation of Relative Camera Positions for Uncalibrated Cameras , 1992, ECCV.

[3]  Carlo Tomasi,et al.  Good features to track , 1994, 1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[4]  Cordelia Schmid,et al.  Local Grayvalue Invariants for Image Retrieval , 1997, IEEE Trans. Pattern Anal. Mach. Intell..

[5]  Sebastian Thrun,et al.  Learning Metric-Topological Maps for Indoor Mobile Robot Navigation , 1998, Artif. Intell..

[6]  Shree K. Nayar,et al.  Ego-motion and omnidirectional cameras , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).

[7]  Bernhard Schölkopf,et al.  Where did I take that snapshot? Scene-based homing by image matching , 1998, Biological Cybernetics.

[8]  Reinhard Koch,et al.  Matching of affinely invariant regions for visual servoing , 1999, Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C).

[9]  Luc Van Gool,et al.  Recognizing color patterns irrespective of viewpoint and illumination , 1999, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149).

[10]  David G. Lowe,et al.  Object recognition from local scale-invariant features , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[11]  Adam Baumberg,et al.  Reliable feature matching across widely separated views , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[12]  Jun Rekimoto,et al.  CyberCode: designing augmented reality environments with visual tags , 2000, DARE '00.

[13]  Daniel G. Aliaga.  Accurate Catadioptric Calibration for Real-time Pose Estimation of Room-size Environments , 2001, ICCV.

[14]  Antonis A. Argyros,et al.  Robot homing based on corner tracking in a sequence of panoramic images , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[15]  Hendrik Van Brussel,et al.  Shared Autonomy for Wheel Chair Control: Attempts to Assess the User's Autonomy , 2001, AMS.

[16]  Cordelia Schmid,et al.  An Affine Invariant Interest Point Detector , 2002, ECCV.

[17]  Jiri Matas,et al.  Robust wide-baseline stereo from maximally stable extremal regions , 2004, Image Vis. Comput..

[18]  Hans J. Schneebeli,et al.  A general approach for egomotion estimation with omnidirectional images , 2002, Proceedings of the IEEE Workshop on Omnidirectional Vision 2002. Held in conjunction with ECCV'02.

[19]  Andrew J. Davison,et al.  Real-time simultaneous localisation and mapping with a single camera , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.

[20]  Hendrik Van Brussel,et al.  Fine Motion Planning for Shared Wheelchair Control: Requirements and Preliminary Experiments , 2003 .

[21]  Kostas Daniilidis,et al.  Mirrors in motion: epipolar geometry and motion estimation , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.

[22]  Stefan B. Williams,et al.  Reduced SIFT Features For Image Retrieval And Indoor Localisation , 2004 .

[23]  Tinne Tuytelaars,et al.  Fast wide baseline matching for visual navigation , 2004, CVPR 2004.

[24]  James R. Bergen,et al.  Visual odometry , 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..

[25]  Luc Van Gool,et al.  Markerless computer vision based localization using automatically generated topological maps , 2004 .

[26]  Ehud Rivlin,et al.  Visual Homing: Surfing on the Epipoles , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).

[27]  T. S. Collett,et al.  Landmark maps for honeybees , 1987, Biological Cybernetics.

[28]  Luc Van Gool,et al.  Vision Based Intelligent Wheel Chair Control: The Role of Vision and Inertial Sensing in Topological Navigation , 2004, J. Field Robotics.

[29]  Luc Van Gool,et al.  Vision Based Intelligent Wheel Chair Control: The Role of Vision and Inertial Sensing in Topological Navigation , 2004 .

[30]  Michel Dhome,et al.  Towards an alternative GPS sensor in dense urban environment from visual memory , 2004, BMVC.

[31]  Josechu J. Guerrero,et al.  Visual correction for mobile robot homing , 2005, Robotics Auton. Syst..

[32]  Domenico Prattichizzo,et al.  Epipole-Based Visual Servoing with Central Catadioptric Camera , 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.

[33]  Luc Van Gool,et al.  Feature based omnidirectional sparse visual path following , 2005, 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[34]  Robert M. Haralick,et al.  Review and analysis of solutions of the three point perspective pose estimation problem , 1994, International Journal of Computer Vision.

[35]  Frédéric Labrosse,et al.  Visual homing: a purely appearance-based approach , 2006 .