Observability analysis and optimal information gathering of mobile robot navigation system

Observability and motion planning based on optimal information gathering of mobile robot navigation system is considered in this paper. In order to obtain the minimum standard of observable for the bearing-only mobile robot navigation system, the observability is analyzed in this paper. It is known that the observability analysis can only be used to illustrate the observable condition of mobile robot localization system. However it cannot be used to illustrate which observation is the best for observability. As a result, entropy based optimal information gathering method is introduced in this paper and is used to evaluate the effectiveness and difference of the different observations. Simulation results are presented to verify the effectiveness of the proposed optimal information gathering method.

[1]  Roland Siegwart,et al.  Observability analysis for mobile robot localization , 2005, 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[2]  S. Sukkarieh,et al.  Observability analysis and active control for airborne SLAM , 2008, IEEE Transactions on Aerospace and Electronic Systems.

[3]  Randal W. Beard,et al.  Bearing-only Cooperative Localization , 2013, J. Intell. Robotic Syst..

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

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

[6]  Suyong Yeon,et al.  Observability analysis of 2D geometric features using the condition number for SLAM applications , 2013, 2013 13th International Conference on Control, Automation and Systems (ICCAS 2013).

[7]  Stergios I. Roumeliotis,et al.  Observability-based consistent EKF estimators for multi-robot cooperative localization , 2011, Auton. Robots.

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

[9]  Stergios I. Roumeliotis,et al.  Analysis and improvement of the consistency of extended Kalman filter based SLAM , 2008, 2008 IEEE International Conference on Robotics and Automation.

[10]  Arthur C. Sanderson,et al.  A distributed algorithm for cooperative navigation among multiple mobile robots , 1997, Adv. Robotics.

[11]  Agostino Martinelli.  Local decomposition and observability properties for automatic calibration in mobile robotics , 2009, 2009 IEEE International Conference on Robotics and Automation.

[12]  Gaurav S. Sukhatme,et al.  Localization for mobile robot teams using maximum likelihood estimation , 2002, IEEE/RSJ International Conference on Intelligent Robots and Systems.

[13]  Randal W. Beard,et al.  Graph-Based Observability Analysis of Bearing-Only Cooperative Localization , 2012, IEEE Transactions on Robotics.

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

[15]  Stergios I. Roumeliotis,et al.  Distributed multirobot localization , 2002, IEEE Trans. Robotics Autom..

[16]  Todd E. Humphreys,et al.  Motion planning for optimal information gathering in opportunistic navigation systems , 2013 .

[17]  Stergios I. Roumeliotis,et al.  Performance analysis of multirobot Cooperative localization , 2006, IEEE Transactions on Robotics.

[18]  Wolfram Burgard,et al.  A Probabilistic Approach to Collaborative Multi-Robot Localization , 2000, Auton. Robots.

[19]  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.

[20]  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..

[21]  P HuangGuoquan,et al.  Observability-based consistent EKF estimators for multi-robot cooperative localization , 2011 .

[22]  Antonio Bicchi,et al.  A Complete Observability Analysis of the Planar Bearing Localization and Mapping for Visual Servoing with Known Camera Velocities , 2013 .