Abstract
This paper proposes methods to fuse range images and intensity images which are measured from multiple view points. Distributed sensing is a key technology for multiple robot system. As sensory information for the robot system, range image and intensity image are both useful and complementary, and thus fusion of the two images is thought to be effective. In this paper, each robot is assumed to have both range image sensor and intensity image sensor, and measures planar regions, 3D edges, cylindrical regions by fusing a range image and an intensity image. Methods to fuse such features which are measured from multiple view points by multiple robots are proposed. They are formulated by the least square approach, considering the errors of position and orientation of each robot and the errors of images. Experiments are performed to show the effectiveness of the proposed fusion methods.
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.
Similar content being viewed by others
References
Hebert, M., Krotkov, E.: “3-D Measurements From Imaging Laser Radars: How Good Are They?,” IEEE/RSJ Int. Workshop on Intelligent Robots and Systems ‘81, pp. 359–364, 1991.
Sorimachi, K.: “Active range pattern sensor,” J. Robotics Mechatronics, 1, pp. 269–273, 1989.
Sato, K., Yokoyama A. and Inokuchi, S.: “ Silicon range finder - a realtime range finding VLSI,” Proc. Custom Integrated Circuits Conf., 1994.
Kanade, T, Gruss, A. and Carley, L.R.: “A VLSI sensor based rangefinding system”, Robotics Research Fifth International Symposium, pp. 49–56, 1990.
Kanade, T., Kano, H., Kimura, S., Yoshida, A. and Oda, K.: “Development of a video-rate stereo machine,” Proc. IEEE Int. Conf. on IROS’95, Vol. 3, pp. 95–100, 1995.
Luo, R.C. and Kay, M.G.: “Multi-sensor data fusion system for intelligent robots,” IEEE Trans. on Syst., M.n. Cybern., 19, 5, pp. 901–931, 1989.
Kadono, K., Asada, M. and Shirai, Y: “Context-constrained matching of hierarchical CAD-based models for outdoor scene interpretation,” Proc IEEE Workshop on Directions in Automated CAD-Based Vision, pp. 186–195, 1991.
Devy, M. and Boumaza, R.: “Multi-Sensory Fusion and Model-Based Recognition of Complex Objects,” Proc. IEEE Int. Conf. on MFI’94, pp. 345–352, 1994.
Nakazawa, K. and Oshita, T.: “Position Control of Vision Based Robot Hand -Fusion of 2-D Image and Discrete Range Image by Multi-Agent-,” Proc. IEEE Int. Conf. on MFI’94, pp. 353359, 1994.
Umeda, K., Arai, T., Tabuchi, M. and Ikushima, K.: “ Strategy and fundamental algorithms of fusing range image and intensity image for object recognition,” Proc. IEEE Int. Conf. on IROS’95, Vol. 3, pp. 216–221, 1995.
Umeda, K., Arai, T. and Ikushima, K.: “Fusion of Range Image and Intensity Image for 3D Shape Recognition,” Proc. 1996 IEEE Int. Conf. on Robotics and Automation, Vol.1, pp. 680685, 1996.
Umeda, K. and Arai, T.: “ Industrial Vision System by Fusing Range Image and Intensity Image,” Proc. IEEE Int. Conf. on MFI’94, pp. 337–344, 1994.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1996 Springer Japan
About this paper
Cite this paper
Umeda, K., Ikushima, K. (1996). Fusion of Range Images and Intensity Images Measured from Multiple View Points. In: Asama, H., Fukuda, T., Arai, T., Endo, I. (eds) Distributed Autonomous Robotic Systems 2. Springer, Tokyo. https://doi.org/10.1007/978-4-431-66942-5_36
Download citation
DOI: https://doi.org/10.1007/978-4-431-66942-5_36
Publisher Name: Springer, Tokyo
Print ISBN: 978-4-431-66944-9
Online ISBN: 978-4-431-66942-5
eBook Packages: Springer Book Archive