Abstract
Perception remains a challenge in outdoor environments. Overcoming the limitations of vision-based sensors, microwave radar presents considerable potential. Such a sensor so-called K2Pi has been designed for environment mapping. In order to build radar maps, an algorithm named R-SLAM has been developed. The global radar map is constructed through a data merging process, using map matching of successive radar image sequences. An occupancy grid approach is used to describe the environment. First results obtained in urban and natural environments are presented, which show the ability of the microwave radar to deal with extended environments.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Scheding, S., Brooker, G.V., Bishop, M., Maclean, A.: Terrain imaging and perception using millimeter wave radar. In: Proceedings of the 2002 Australasian Conference on Robotics and Automation, Australia (2002)
Brooker, G.: Millimeter Wave Radar for Tracking and Imaging applications. In: 1st International Conference on Sensing technology, New Zealand (2005)
Foessel, A., Bares, J., Whittaker, W.: Three dimensional map building with mmw radar. In: Proceedings of the 3rd International Conference on Field and Service Robotics, Finland (2001)
Clark, S., Durran-Whyte, H.: The design of a high performance mmw radar system for autonomous land vehicle navigation. In: Proceedings of the International Conference on Field and Service Robotics, pp. 292–299 (1997)
Jose, E., Adams, M.: Millimeter Wave RADAR Spectra Simulation and Interpretation for Outdoor SLAM. In: IEEE International Conference on Robotics & Automation, New Orleans, USA (2004)
Dissanayake, G., Newman, P., Durrant-Whyte, H.F., Clark, S., Csobra, M.: A solution to the simultaneous localization and map building (SLAM) problem. IEEE Transactions on Robotics and Automation 17(3), 229–241 (2001)
Fang, H., Fan, R., Thuilot, B., Martinet, P.: Trajectory Tracking Control of Farm Vehicles in Presence of Sliding. Robotics and Autonomous Systems 54(10), 828–839 (2006)
Bryson, L.S., Mayard, C., Castro-Lacouture, D., Williams, R.L.: Fully autonomous robot for paving operations. In: Conference Proceedings of the ASCE Congress, vol. 37 (2005)
Marques, C., Cristovao, J., Lima, P., Frazao, J., Ribeiro, I., Ventura, R.: RAPOSA: Semi-Autonomous Robot for Rescue Operations. In: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), China (2006)
Skolnik, M.I.: Introduction to radar systems. Electrical Engineering Series. McGraw-Hill International Editions, New York (1980)
Monod, M.O.: Frequency modulated radar: a new sensor for natural environment and mobile robotics. Ph.D. Thesis, Paris VI University, France (1995)
Wang, M.: Localization estimation and uncertainty analysis for mobile robots. In: IEEE International Conference on Robotics and Automation, pp. 1230–1235 (1988)
Frost, V.S., Stiles, J.A., Shanmugan, K.S., Holtzman, J.C.: A model for radar images and its application to adaptive signal filtering of multiplicative noise. IEEE Transactions on Pattern Analysis and Machine Intelligence 4(2), 157–165 (1982)
Lee, J.S., Jurkevich, I., Dawaele, P., Wambacq, P., Oosterlinck, A.: Speckle filtering of synthetic aperture radar images: A review. Remote Sensing Reviews 8, 313–340 (1994)
Guoqing, L., Shunji, H., Hong, X., Torre1, A., Rubertone, F.: Study on speckle reduction in multi-look polarimetric SAR image. Journal of Electronics 16(1) (1999)
Martin, M., Moravec, H.: Robot Evidence Grids. Technical Report CMU-RI-TR-96-06, Robotics Institute. Carnegie Mellon University, Pittsburgh (1996)
Chandran, M., Newman, P.: Motion Estimation from Map Quality with Millimeter Wave Radar. In: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), China, pp. 808–813 (2006)
Chen, Z., Samarabandu, J., Rodrigo, R.: Recent advances in simultaneous localization and map-building using computer vision. Advanced Robotics 21(3), 233–265 (2007)
Jose, E., Adams, M.: Relative RADAR Cross Section based Feature Identification with Millimetre Wave RADAR for Outdoor SLAM. In: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Japan (2004)
Brooker, G.: Correlation of Millimetre Wave Radar Images with Aerial Photographs for Autonomous Navigation of a UAV. In: 2nd International Conference on Sensing Technology, Palmerston North, New Zealand (2007)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Rouveure, R., Faure, P., Monod, MO. (2009). Radar Imager for Perception and Mapping in Outdoor Environments. In: Blanc-Talon, J., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2009. Lecture Notes in Computer Science, vol 5807. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04697-1_58
Download citation
DOI: https://doi.org/10.1007/978-3-642-04697-1_58
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-04696-4
Online ISBN: 978-3-642-04697-1
eBook Packages: Computer ScienceComputer Science (R0)