Trajectory-oriented EKF-SLAM using the fourier-mellin transform applied to microwave radar images

Authors:
Franck Gérossier;Paul Checchin;Christophe Blanc;Roland Chapuis;Laurent Trassoudaine
Affiliations:
-;-;-;-;-
Venue:
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Year:
2009

Citing 12
Cited 0

A Method for Registration of 3-D Shapes

IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part II
Symmetric Phase-Only Matched Filtering of Fourier-Mellin Transforms for Image Registration and Recognition

IEEE Transactions on Pattern Analysis and Machine Intelligence
Robot Pose Estimation in Unknown Environments by Matching 2D Range Scans

Journal of Intelligent and Robotic Systems
Simultaneous localization, mapping and moving object tracking

Simultaneous localization, mapping and moving object tracking
A Discussion of Simultaneous Localization and Mapping

Autonomous Robots
Recursive scan-matching SLAM

Robotics and Autonomous Systems
Including probabilistic target detection attributes into map representations

Robotics and Autonomous Systems
Square Root SAM: Simultaneous Localization and Mapping via Square Root Information Smoothing

International Journal of Robotics Research
Map Matching and Data Association for Large-Scale Two-dimensional Laser Scan-based SLAM

International Journal of Robotics Research
A perception-driven autonomous urban vehicle

Journal of Field Robotics - Special Issue on the 2007 DARPA Urban Challenge, Part III
Efficient View-Based SLAM Using Visual Loop Closures

IEEE Transactions on Robotics
An FFT-based technique for translation, rotation, and scale-invariant image registration

IEEE Transactions on Image Processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper is concerned with the Simultaneous Localization And Mapping (SLAM) application using data obtained from a microwave radar sensor. The radar scanner is based on the Frequency Modulated Continuous Wave (FMCW) technology. In order to overcome the complexity of radar image analysis, a trajectory-oriented EKF-SLAM technique using data from a 360° field of view radar sensor has been developed. This process makes no landmark assumptions and avoids the data association problem. The method of egomotion estimation makes use of the Fourier-Mellin Transform for registering radar images in a sequence, from which the rotation and translation of the sensor motion can be estimated. In the context of the scan-matching SLAM, the use of the Fourier-Mellin Transform is original and provides an accurate and efficient way of computing the rigid transformation between consecutive scans. Experimental results on real-world data are presented. Moreover a performance evaluation of the results is carried out. A comparative study between the output data of the proposed method and the data processed with smoothing approaches to SLAM is also achieved.