A Complete Observability Analysis of the Planar Bearing Localization and Mapping for Visual Servoing with Known Camera Velocities

This paper presents an analysis of planar bearing localization and mapping for visual servoing with known camera velocities. In particular, we investigate what is the subset of camera locations and environmental features that can be retrieved from dynamic observations obtained by a planar bearing sensor (nearly e.g., a pinhole camera). Results assume that the camera's linear and angular velocities are available, which is equivalent to consider a unicycle vehicle carrying an onboard camera. Results hold if other system inputs are considered, e.g., an omnidirectional vehicle. The theoretical results may guide the design of nonlinear observers to estimate the variables of interest in real time to be applied to visual servoing schemes. An example of such an observer is discussed and simulated.

[1]  Antonio Bicchi,et al.  Unicycle-like Robots with Eye-in-Hand Monocular Cameras: From PBVS towards IBVS , 2010 .

[2]  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..

[3]  Peter I. Corke Mobile Robot Navigation As A Planar Visual Servoing Problem , 2001, ISRR.

[4]  Wilfrid Perruquetti,et al.  A single landmark based localization algorithm for non-holonomic mobile robots , 2011, 2011 IEEE International Conference on Robotics and Automation.

[5]  Stefano Soatto,et al.  3-D Structure from Visual Motion: Modeling, Representation and Observability , 1997, Autom..

[6]  James J. Little,et al.  Mobile Robot Localization and Mapping with Uncertainty using Scale-Invariant Visual Landmarks , 2002, Int. J. Robotics Res..

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

[8]  Antonio Bicchi,et al.  Visual Servoing on Image Maps , 2006, ISER.

[9]  Antonio Bicchi,et al.  3 known landmarks are enough for solving planar bearing SLAM and fully reconstruct unknown inputs , 2010, 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[10]  Antonio Bicchi,et al.  ON THE OBSERVABILITY OF MOBILE VEHICLE LOCALIZATION , 1999 .

[11]  Patrick Rives,et al.  An Efficient Direct Approach to Visual SLAM , 2008, IEEE Transactions on Robotics.

[12]  Antonio Bicchi,et al.  On the observability of mobile vehicles localization , 1998 .

[13]  Bernhard P. Wrobel,et al.  Multiple View Geometry in Computer Vision , 2001 .

[14]  R. Siegwart,et al.  Observability Properties and Optimal Trajectories for On-line Odometry Self-Calibration , 2006, Proceedings of the 45th IEEE Conference on Decision and Control.

[15]  A. Krener,et al.  Nonlinear controllability and observability , 1977 .

[16]  James R. Bergen,et al.  Visual odometry for ground vehicle applications , 2006, J. Field Robotics.

[17]  Antonio Bicchi,et al.  On The Problem of Simultaneous Localization, Map Building, and Servoing of Autonomous Vehicles , 2004, Advances in Control of Articulated and Mobile Robots.

[18]  Yi Xiao,et al.  Research on unobservability problem for two-dimensional bearings-only target motion analysis , 2005, Proceedings of 2005 International Conference on Intelligent Sensing and Information Processing, 2005..