VISION-BASED MOBILE ROBOT NAVIGATION

This paper presents a vision-based navigation system for mobile robots. It enables the robot to build a map of its environment, localize efficiently itself without use of any artificial markers or other modifications, and navigate without colliding with obstacles. The Simultaneous Localization And Mapping (SLAM) procedure builds a global representation of the environment based on several size limited local maps built using the approach introduced by Davison [1]. Two methods for global map are presented; the first method consists in transforming each local map into a global frame before to start building a new local map. While in the second method, the global map consists only in a set of robot positions where new local maps are started (i.e. the base references of the local maps). In both methods, the base frame for the global map is the robot position at instant . Based on the estimated map and its global position, the robot can find a path and navigate without colliding with obstacles to reach a goal defined the user. The moving objects in the scene are detected and their motion is estimated using a combination of Gaussian Mixture Model (GMM) background subtraction approach and a Maximum a Posteriori Probability Markov Random Field (MAP-MRF) framework [2]. Experimental results in real scenes are presented to illustrate the effectiveness of the proposed method. t0

[1]  Hugh F. Durrant-Whyte,et al.  Mobile robot localization by tracking geometric beacons , 1991, IEEE Trans. Robotics Autom..

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

[3]  Bum-Jae You,et al.  Visual navigation for indoor mobile robots using a single camera , 2005, 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[4]  Kaijen Hsiao,et al.  Mapping Contoured Terrain: A Comparison of SLAM Algorithms for Radio-Controlled Helicopters , 2005 .

[5]  Hugh F. Durrant-Whyte,et al.  A solution to the simultaneous localization and map building (SLAM) problem , 2001, IEEE Trans. Robotics Autom..

[6]  Amit Singhal,et al.  Issues in Autonomous Mobile Robot Navigation , 1997 .

[7]  Olivier Stasse,et al.  MonoSLAM: Real-Time Single Camera SLAM , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[8]  Heiko Neumann,et al.  Robot navigation by combining central and peripheral optical flow detection on a space-variant map , 1998, Proceedings. Fourteenth International Conference on Pattern Recognition (Cat. No.98EX170).

[9]  George A. Bekey,et al.  AUTONOMOUS ROBOTS, From Biological Inspiration to Implementation and Control, by G.A. Bekey, MIT Press, 2005, xv + 577 pp., index, ISBN 0-262-02578-7, 25 pages of references (Hb. £35.95) , 2005, Robotica.

[10]  Henrik I. Christensen,et al.  Graphical SLAM using vision and the measurement subspace , 2005, 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[11]  Hichem Sahli,et al.  CoRoBa, a Multi Mobile Robot Control and Simulation Framework , 2006 .

[12]  John J. Leonard,et al.  A Computationally Efficient Method for Large-Scale Concurrent Mapping and Localization , 2000 .

[13]  Hugh Durrant-Whyte,et al.  Toward Deployment of Large Scale Simultaneous Localisation and Map Building (SLAM) Systems , 2000 .

[14]  A. Gürcan,et al.  Technical Report on Autonomous Mobile Robot navigation , 2009 .

[15]  M. Gini,et al.  Visual servoing of a miniature robot toward a marked target , 2002, 2002 14th International Conference on Digital Signal Processing Proceedings. DSP 2002 (Cat. No.02TH8628).

[16]  Alberto Sanfeliu,et al.  Concurrent map building and localization with landmark validation , 2002, Object recognition supported by user interaction for service robots.

[17]  Wolfram Burgard,et al.  A Probabilistic Approach to Concurrent Mapping and Localization for Mobile Robots , 1998, Auton. Robots.

[18]  Hugh F. Durrant-Whyte,et al.  Simultaneous Localization and Mapping with Sparse Extended Information Filters , 2004, Int. J. Robotics Res..

[19]  Eric Foxlin,et al.  Generalized architecture for simultaneous localization, auto-calibration, and map-building , 2002, IEEE/RSJ International Conference on Intelligent Robots and Systems.

[20]  John J. Leonard,et al.  Robust Mapping and Localization in Indoor Environments Using Sonar Data , 2002, Int. J. Robotics Res..

[21]  Andrea Bonarini.  Delayed Reinforcement , Fuzzy Q-Learning and Fuzzy Logic Controllers , 1996 .

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

[23]  Jean-Arcady Meyer,et al.  A biomimetic reactive navigation system using the optical flow for a rotary-wing UAV in urban environment , 2004 .

[24]  Steve Vinoski,et al.  Advanced CORBA® Programming with C++ , 1999 .

[25]  Ju-Jang Lee,et al.  Self-Learning Fuzzy Logic Controller using Q-Learning , 2000, J. Adv. Comput. Intell. Intell. Informatics.

[26]  Hobart R. Everett,et al.  Where am I?" sensors and methods for mobile robot positioning , 1996 .

[27]  Yolanda González Cid,et al.  Real-time 3d SLAM with wide-angle vision , 2004 .

[28]  Li-Xin Wang,et al.  Adaptive fuzzy systems and control , 1994 .

[29]  Takeo Kanade,et al.  An Iterative Image Registration Technique with an Application to Stereo Vision , 1981, IJCAI.

[30]  Hichem Sahli,et al.  Tele-robot with shared autonomy: Distributed navigation development framework , 2006, Integr. Comput. Aided Eng..

[31]  N. Franceschini,et al.  From insect vision to robot vision , 1992 .

[32]  Hichem Sahli,et al.  MRF-Based Foreground Detection in Image Sequences from a Moving Camera , 2006, 2006 International Conference on Image Processing.

[33]  Giuseppina C. Gini,et al.  Indoor Robot Navigation With Single Camera Vision , 2002, PRIS.

[34]  Bruce Blumberg.  Go with the flow: synthetic vision for autonomous animated creatures , 1997, AGENTS '97.

[35]  Illah R. Nourbakhsh,et al.  Techniques for evaluating optical flow for visual odometry in extreme terrain , 2004, 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566).

[36]  John J. Leonard,et al.  Cooperative concurrent mapping and localization , 2002, Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292).