Mobile robot motion estimation by 2D scan matching with genetic and iterative closest point algorithms
Version of Record online: 26 JAN 2006
Copyright © 2006 John Wiley & Sons, Inc.
Journal of Field Robotics
Volume 23, Issue 1, pages 21–34, January 2006
How to Cite
Martínez, J. L., González, J., Morales, J., Mandow, A. and García-Cerezo, A. J. (2006), Mobile robot motion estimation by 2D scan matching with genetic and iterative closest point algorithms. J. Field Robotics, 23: 21–34. doi: 10.1002/rob.20104
- Issue online: 26 JAN 2006
- Version of Record online: 26 JAN 2006
- Manuscript Accepted: 15 OCT 2005
- Manuscript Received: 4 AUG 2005
The paper reports on mobile robot motion estimation based on matching points from successive two-dimensional (2D) laser scans. This ego-motion approach is well suited to unstructured and dynamic environments because it directly uses raw laser points rather than extracted features. We have analyzed the application of two methods that are very different in essence: (i) A 2D version of iterative closest point (ICP), which is widely used for surface registration; (ii) a genetic algorithm (GA), which is a novel approach for this kind of problem. Their performance in terms of real-time applicability and accuracy has been compared in outdoor experiments with nonstop motion under diverse realistic navigation conditions. Based on this analysis, we propose a hybrid GA-ICP algorithm that combines the best characteristics of these pure methods. The experiments have been carried out with the tracked mobile robot Auriga-α and an on-board 2D laser scanner. © 2006 Wiley Periodicals, Inc.