High-Resolution Ultrasonic Environment Imaging

This paper presents a novel approach to high-resolution ultrasonic environment imaging for autonomous mobile systems. It describes the fusion of sensor data from multiple wide-angled ultrasonic transducers with overlapping detection cones for creating local environment models. A fitting technique defined as tangential regression is introduced that considers sensor properties as well as physical reflection properties of ultrasound. This allows a reliable detection and localization of straight-line segments which describe the boundary of geometric objects. Experimental results show that straight-line segments extracted at different robot locations can be aggregated and merged in order to obtain a global environment map

[1]  Dirk Bank,et al.  High-resolution ultrasonic sensing for autonomous mobile systems , 2007 .

[2]  Etienne Colle,et al.  Real-time localisation of a low-cost mobile robot with poor ultrasonic data , 1998 .

[3]  James L. Crowley.  Dynamic world modeling for an intelligent mobile robot using a rotating ultra-sonic ranging device , 1985, Proceedings. 1985 IEEE International Conference on Robotics and Automation.

[4]  Herbert Peremans,et al.  Tri-aural perception on a mobile robot , 1993, [1993] Proceedings IEEE International Conference on Robotics and Automation.

[5]  Thomas Kämpke,et al.  Polygonal Model Fitting , 2001, J. Intell. Robotic Syst..

[6]  Michael R. M. Jenkin,et al.  Multi-transducer sonar interpretation , 1993, [1993] Proceedings IEEE International Conference on Robotics and Automation.

[7]  J. Forsberg,et al.  The Hough transform inside the feedback loop of a mobile robot , 1993, [1993] Proceedings IEEE International Conference on Robotics and Automation.

[8]  Giuseppe Carlo Calafiore.  Outliers robustness in multivariate orthogonal regression , 2000, IEEE Trans. Syst. Man Cybern. Part A.

[9]  Adam Krzyzak,et al.  A Polygonal Line Algorithm for Constructing Principal Curves , 1998, NIPS.

[10]  James L. Crowley,et al.  World modeling and position estimation for a mobile robot using ultrasonic ranging , 1989, Proceedings, 1989 International Conference on Robotics and Automation.

[11]  Michael K. Brown,et al.  Feature extraction techniques for recognizing solid objects with an ultrasonic range sensor , 1985, IEEE J. Robotics Autom..

[12]  Hauke Schmidt,et al.  INTERFERENCE CANCELATION IN ULTRASONIC SENSOR ARRAYS BY STOCHASTIC CODING AND ADAPTIVE FILTERING , 1998 .

[13]  Viii Supervisor.  Sonar-Based Real-World Mapping and Navigation , 2001 .

[14]  Yoram Koren,et al.  The vector field histogram-fast obstacle avoidance for mobile robots , 1991, IEEE Trans. Robotics Autom..

[15]  Billur Barshan,et al.  Surface Profile Determination from Multiple Sonar Data Using Morphological Processing , 1999, Int. J. Robotics Res..

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

[17]  O. Wijk.  Triangulation Based Fusion of Sonar Data with Application in Mobile Robot Mapping and Localization , 2001 .

[18]  Lindsay Kleeman,et al.  Mobile Robot Sonar for Target Localization and Classification , 1995, Int. J. Robotics Res..

[19]  Bernt Schiele,et al.  A comparison of position estimation techniques using occupancy grids , 1994, Proceedings of the 1994 IEEE International Conference on Robotics and Automation.

[20]  Ben J. A. Kröse,et al.  Accurate estimation of environment parameters from ultrasonic data , 1993, Robotics Auton. Syst..

[21]  D. Bank.  A novel ultrasonic sensing system for autonomous mobile systems , 2002 .

[22]  Michael Drumheller,et al.  Mobile Robot Localization Using Sonar , 1987, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[23]  John J. Leonard,et al.  Directed Sonar Sensing for Mobile Robot Navigation , 1992 .

[24]  I N Bronstein,et al.  Taschenbuch der Mathematik , 1966 .

[25]  Kostas J. Kyriakopoulos,et al.  Simultaneous localization and map building for mobile robot navigation , 1999, IEEE Robotics Autom. Mag..

[26]  Phillip J. McKerrow.  Echolocation - From range to outline segments , 1993, Robotics Auton. Syst..