Rao-Blackwellized Particle Smoothing for Occupancy-Grid Based SLAM Using Low-Cost Sensors

We approach the simultaneous localization and mapping problem by using an ultrasound sensor and wheel encoders on a mobile robot. The measurements are modeled to yield a conditionally linear model for all the map states. Moreover, we implement a Rao-Blackwellized particle smoother (RBPS) for jointly estimating the position of the robot and the map. The method is applied and successfully verified by experiments on a small Lego robot where ground truth was obtained by the use of a VICON real-time positioning system. The results show that the RBPS contributes with more robust estimates at the cost of computational complexity and memory usage.

[1]  Wolfgang D. Rencken,et al.  Concurrent localisation and map building for mobile robots using ultrasonic sensors , 1993, Proceedings of 1993 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '93).

[2]  Wolfram Burgard,et al.  Sonar-Based Mapping of Large-Scale Mobile Robot Environments using EM , 1999, ICML.

[3]  Thomas B. Schön,et al.  Marginalized particle filters for mixed linear/nonlinear state-space models , 2005, IEEE Transactions on Signal Processing.

[4]  Sebastian Thrun,et al.  Robotic mapping: a survey , 2003 .

[5]  A. Doucet,et al.  Particle filtering for partially observed Gaussian state space models , 2002 .

[6]  D. Fox,et al.  Sonar-Based Mapping With Mobile Robots Using EM , 1999 .

[7]  Wolfram Burgard,et al.  Improving Grid-based SLAM with Rao-Blackwellized Particle Filters by Adaptive Proposals and Selective Resampling , 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.

[8]  H. Durrant-Whyte,et al.  Simultaneous Localisation and Mapping ( SLAM ) : Part II State of the Art , 2006 .

[9]  Simon J. Godsill,et al.  On sequential Monte Carlo sampling methods for Bayesian filtering , 2000, Stat. Comput..

[10]  Thomas Bo Schön,et al.  Rao-Blackwellised particle smoothers for mixed linear / nonlinear state-space models , 2011 .

[11]  Beom Hee Lee,et al.  Analysis of Resampling Process for the Particle Depletion Problem in FastSLAM , 2007, RO-MAN 2007 - The 16th IEEE International Symposium on Robot and Human Interactive Communication.

[12]  Simon J. Godsill,et al.  Rao-Blackwellized particle smoothers for mixed linear/nonlinear state-space models , 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.

[13]  S. Godsill,et al.  A Backward-Simulation Based Rao-Blackwellized Particle Smoother for Conditionally Linear Gaussian Models , 2012 .

[14]  Peter C. Cheeseman,et al.  Estimating uncertain spatial relationships in robotics , 1986, Proceedings. 1987 IEEE International Conference on Robotics and Automation.

[15]  Petros G. Voulgaris,et al.  On optimal ℓ∞ to ℓ∞ filtering , 1995, Autom..

[16]  Hugh F. Durrant-Whyte,et al.  Simultaneous localization and mapping: part I , 2006, IEEE Robotics & Automation Magazine.

[17]  Jerker Nordh,et al.  pyParticleEst: A Python Framework for Particle-Based Estimation Methods , 2017 .

[18]  Oussama Khatib,et al.  Springer Handbook of Robotics , 2007, Springer Handbooks.

[19]  Hugh Durrant-Whyte,et al.  Simultaneous localization and mapping (SLAM): part II , 2006 .

[20]  Wolfram Burgard,et al.  Improved Techniques for Grid Mapping With Rao-Blackwellized Particle Filters , 2007, IEEE Transactions on Robotics.

[21]  Wan Kyun Chung,et al.  A practical approach for EKF-SLAM in an indoor environment: fusing ultrasonic sensors and stereo camera , 2008, Auton. Robots.

[22]  Ingemar J. Cox,et al.  Dynamic Map Building for an Autonomous Mobile Robot , 1990, EEE International Workshop on Intelligent Robots and Systems, Towards a New Frontier of Applications.

[23]  Ronald Parr,et al.  DP-SLAM: fast, robust simultaneous localization and mapping without predetermined landmarks , 2003, IJCAI 2003.

[24]  Karl Berntorp,et al.  Extending the Occupancy Grid Concept for Low-Cost Sensor Based SLAM , 2012, SyRoCo.

[25]  Wolfram Burgard,et al.  An efficient fastSLAM algorithm for generating maps of large-scale cyclic environments from raw laser range measurements , 2003, Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03CH37453).