Projet IMPALA. Radar panoramique hyperfréquence pour la localisation et la cartographie simultanées en environnement extérieur

L'objectif du projet IMPALA est d'evaluer l'apport du radar comme solution alternative aux moyens de perception en robotique mobile d'exterieur. Cet article illustre a travers une application de localisation et de cartographie simultanees (SLAM). les potentialites d'un radar panoramique a modulation de frequence (FMCW) qui a ete developpe au cours du projet. Donnant acces a l'information de distance et de vitesse des entites mobiles presentes dans l'environnement, le radar permet d'envisager des applications de detection et de suivi d'objets mobiles (DATMO) dont un premier resultat est presente ici.

[1]  Roland Chapuis,et al.  Radar Scan Matching SLAM Using the Fourier-Mellin Transform , 2009, FSR.

[2]  Edwin Olson,et al.  Real-time correlative scan matching , 2009, 2009 IEEE International Conference on Robotics and Automation.

[3]  Martin David Adams,et al.  Including probabilistic target detection attributes into map representations , 2007, Robotics Auton. Syst..

[4]  Andreas Geiger,et al.  Visual odometry based on stereo image sequences with RANSAC-based outlier rejection scheme , 2010, 2010 IEEE Intelligent Vehicles Symposium.

[5]  Sen Zhang,et al.  An Efficient Data Association Approach to Simultaneous Localization and Map Building , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.

[6]  Andrew Howard,et al.  Real-time stereo visual odometry for autonomous ground vehicles , 2008, 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[7]  Paul Checchin,et al.  Odométrie radar par analyse de la distorsion - Application à un véhicule roulant à vitesse élevée , 2012 .

[8]  Paul Newman,et al.  Detecting Loop Closure with Scene Sequences , 2007, International Journal of Computer Vision.

[9]  Hermann Rohling,et al.  Radar CFAR Thresholding in Clutter and Multiple Target Situations , 1983, IEEE Transactions on Aerospace and Electronic Systems.

[10]  M.O. Monod,et al.  High resolution mapping of the environment with a ground-based radar imager , 2009, 2009 International Radar Conference "Surveillance for a Safer World" (RADAR 2009).

[11]  Martin David Adams,et al.  Millimetre Wave RADAR spectra simulation and interpretation for outdoor SLAM , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.

[12]  Gaurav S. Sukhatme,et al.  Towards 3D mapping in large urban environments , 2004, 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566).

[13]  Luke Fletcher,et al.  A perception-driven autonomous urban vehicle , 2008 .

[14]  Hugh F. Durrant-Whyte,et al.  Field and service applications - An autonomous straddle carrier for movement of shipping containers - From Research to Operational Autonomous Systems , 2007, IEEE Robotics & Automation Magazine.

[15]  Gamini Dissanayake,et al.  Simultaneous localisation and map building using millimetre wave radar to extract natural features , 1999, Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C).

[16]  Andrew Hogue,et al.  Progress towards underwater 3D scene recovery , 2010, C3S2E '10.

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

[18]  Roland Chapuis,et al.  On the fly localization and mapping using a 360 ◦ Field-of-View Microwave Radar Sensor , 2009 .

[19]  Philippe Martinet,et al.  Simultaneous Object Pose and Velocity Computation Using a Single View from a Rolling Shutter Camera , 2006, ECCV.

[20]  Pere Ridao,et al.  Underwater SLAM in a marina environment , 2007, 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[21]  Samuel S. Blackman,et al.  Design and Analysis of Modern Tracking Systems , 1999 .

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

[23]  Hugh F. Durrant-Whyte,et al.  An Experimental and Theoretical Investigation into Simultaneous Localisation and Map Building , 1999, ISER.

[24]  Ian D. Reid,et al.  Simultaneous Localisation and Mapping in Dynamic Environments (SLAMIDE) with Reversible Data Associa , 2007, Robotics: Science and Systems.

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

[26]  P. Faure,et al.  Intertwined Linear Frequency Modulated Radar and Simulator for Outdoor Robotics Applications , 2009 .

[27]  Ian D. Reid,et al.  On combining visual SLAM and visual odometry , 2010, 2010 IEEE International Conference on Robotics and Automation.

[28]  Wolfram Burgard,et al.  Towards Mapping of Cities , 2007, Proceedings 2007 IEEE International Conference on Robotics and Automation.

[29]  Wolfram Burgard,et al.  A visual odometry framework robust to motion blur , 2009, 2009 IEEE International Conference on Robotics and Automation.

[30]  Jagath Samarabandu,et al.  Recent advances in simultaneous localization and map-building using computer vision , 2007, Adv. Robotics.

[31]  Michael Bosse,et al.  Map Matching and Data Association for Large-Scale Two-dimensional Laser Scan-based SLAM , 2008, Int. J. Robotics Res..

[32]  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).

[33]  Paul Newman,et al.  Motion Estimation from Map Quality with Millimeter Wave Radar , 2006, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[34]  M.O. Monod,et al.  Mapping of the environment with a high resolution ground-based radar imager , 2008, MELECON 2008 - The 14th IEEE Mediterranean Electrotechnical Conference.

[35]  Bin Yang,et al.  Derivation of the frequency mismatch probability in linear FMCW radar based on target distribution , 2009, 2009 IEEE Radar Conference.