On-line extraction of stable visual landmarks for a mobile robot with stereo vision

This paper proposes a method to extract on-line stable visual landmarks from sensory data obtained by stereo vision so as to adapt to changes of environment. Given a two-dimensional obstacle map, the robot first extracts vertical line segments which are distinct and inside planar surfaces not near boundary edges as they are expected to be observed reliably from various viewpoints. However, the extracted feature information such as position and length include uncertainty due to errors of vision and motion. The robot then reduces the uncertainty by matching the planar surface containing the features to the map. These processes are performed on-line in order to adapt to actual changes of lighting and the scene depending on the robot's view. Experimental results in real scenes show the validity of the proposed method.

[1]  Yoshiaki Shirai,et al.  On-line viewpoint and motion planning for efficient visual navigation under uncertainty , 1999, Robotics Auton. Syst..

[2]  William H. Press,et al.  Numerical Recipes in C, 2nd Edition , 1992 .

[3]  Yoshiaki Shirai,et al.  Planning of vision-based navigation for a mobile robot under uncertainty , 1997, Proceedings of the 1997 IEEE/RSJ International Conference on Intelligent Robot and Systems. Innovative Robotics for Real-World Applications. IROS '97.

[4]  Jin-Jang Leou,et al.  A dynamic programming approach to line segment matching in stereo vision , 1994, Pattern Recognit..

[5]  Olivier D. Faugeras,et al.  Maintaining representations of the environment of a mobile robot , 1988, IEEE Trans. Robotics Autom..

[6]  Jake K. Aggarwal,et al.  Mobile robot self-location using model-image feature correspondence , 1996, IEEE Trans. Robotics Autom..

[7]  Yoshiaki Shirai,et al.  Vision and Motion Planning for a Mobile Robot under Uncertainty , 1997, Int. J. Robotics Res..

[8]  Ingemar J. Cox,et al.  Blanche-an experiment in guidance and navigation of an autonomous robot vehicle , 1991, IEEE Trans. Robotics Autom..

[9]  Gregory Dudek,et al.  Mobile robot localization from learned landmarks , 1998, Proceedings. 1998 IEEE/RSJ International Conference on Intelligent Robots and Systems. Innovations in Theory, Practice and Applications (Cat. No.98CH36190).

[10]  Don Ray Murray,et al.  Selecting stable image features for robot localization using stereo , 1998, Proceedings. 1998 IEEE/RSJ International Conference on Intelligent Robots and Systems. Innovations in Theory, Practice and Applications (Cat. No.98CH36190).

[11]  Wolfram Burgard,et al.  Active Markov localization for mobile robots , 1998, Robotics Auton. Syst..

[12]  Jean-Claude Latombe,et al.  Reliable navigation using landmarks , 1995, Proceedings of 1995 IEEE International Conference on Robotics and Automation.

[13]  Gregory D. Hager,et al.  Image-based prediction of landmark features for mobile robot navigation , 1997, Proceedings of International Conference on Robotics and Automation.

[14]  Günther Schmidt,et al.  Continuous localization for long-range indoor navigation of mobile robots , 1995, Proceedings of 1995 IEEE International Conference on Robotics and Automation.

[15]  P. S. Maybeck,et al.  The Kalman Filter: An Introduction to Concepts , 1990, Autonomous Robot Vehicles.

[16]  Yoshiaki Shirai,et al.  Autonomous visual navigation of a mobile robot using a human-guided experience , 2002, Robotics Auton. Syst..

[17]  William H. Press,et al.  Numerical recipes in C , 2002 .