Hostname: page-component-78c5997874-ndw9j Total loading time: 0 Render date: 2024-11-10T13:36:04.070Z Has data issue: false hasContentIssue false
  • English
  • Français

Real-time determination of a mobile robot's position by linear scanning of a landmark

Published online by Cambridge University Press:  09 March 2009

Jae H. Kim  and
Hyung S. Cho
Jae H. Kim
Affiliation:
Department of Production Engineering, Korea Advanced Institute of Science and Technology, P.O. Box 150, Chongryangri, Seoul (Korea)
Hyung S. Cho
Affiliation:
Department of Production Engineering, Korea Advanced Institute of Science and Technology, P.O. Box 150, Chongryangri, Seoul (Korea)
Get access Rights & Permissions [Opens in a new window]

Summary

For the navigation of a mobile robot, the determination of its absolute location is one of essential tasks. This paper proposes a stripe type landmark which enables us to develop a fast algorithm to calculate the distance and orientation of a camera relative to the landmark. Exact and closed form solution of the camera location is obtained from the geometric relation between the pattern of landmark and its projected image. Since the presented algorithm requires only one row of the mark image, determination of the location can be processed in real-time. In addition, the mark can be identified using the projective invariant of the original mark pattern without any additional patterns. The effect of the error sources on the location determination is analyzed through a series of simulations and experiments. The applicability of the algorithm to mobile robots is discussed using the experimental results.

Keywords

LandmarkMobile robotPosition determinationVision
Type
Article
Information
Robotica , Volume 10 , Issue 4 , July 1992 , pp. 309 - 319
Copyright
Copyright © Cambridge University Press 1992

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1.Larcommbe, M. H. E., “Tracking Stability of Wire Guided Vehicles” Proc. Int. Conf Auto. Guided Veh. Syst,137–144 (06, 1981).Google Scholar
2.McVey, E. S., Drake, K. C. and Inigo, R. M., “Range Measurements by a Mobile Robot using a Navigation Line” IEEE Trans. Pattern Anal. Mach. Intell. PAMI-8, 105–109 (01 1986).CrossRefGoogle Scholar
3.Tsumura, T., “A System for Measuring Current Position and/or Heading of Vehicle” Bull. JSME 25, No. 203 (1982) pp. 821–826.CrossRefGoogle Scholar
4.Arai, T., “Development of the Measuring Equipment for Location and Direction Using Ultrasonic Waves and its Evaluation” Trans. SICE 18, No. 10, 1031–1020 (10 1982).Google Scholar
5.Fujiwara, K., “Guideless Robot Vehicle” Material on Vehicle Automation No. 18, 10–17 (12, 1981).Google Scholar
6.Keller, M. and Tewinkel, G. C., “Space Resection in Photogrammetry” U.S. Coast and Geodetic Survey ESSA Tech. Rep. 32 (1966).Google Scholar
7.Fischler, M. A. and Bolles, R. C., “Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography” Commun. ACM 24, No. 6, 381–395 (06, 1981).CrossRefGoogle Scholar
8.Ganapathy, S., “Decomposition of Transformation Matrices for Robot Vision” Proc. Int. Conf. Robotics130–139 (1984).Google Scholar
9.Lenz, R. K. and Tsai, R. Y., “Calibrating a Cartesian Robot with eye-hand Configuration Independent of Eye-to-hand Relationship” Proc. Computer Vision and Pattern Recognition, Ann Arbor, MI, 67–75 (06 5–9, 1988).Google Scholar
10.Liu, Y. and Huang, T. S., “Determination of Camera Location from 2-D to 3-D Line and Point Correspondences” IEEE Trans. Pattern Analysis Mach. Intell. PAMI-12, No. 1, 28–37 (01, 1990).CrossRefGoogle Scholar
11.Kabuka, M. R. and Arenas, A. E., “Position Verification of a Mobile Robot Using Standard Pattern” IEEE J. of Robotics and Automation RA-3, No. 6, 505–516 (12, 1987).CrossRefGoogle Scholar
12.Fujiwara, N., Yonezawa, T. and Tsumura, T., “Vehicle Position Finding Method by Means of Processing the Image through a Zoom Lens Camera” ISCIE Proc. Japan-USA Symposium on Flexible Automation, Kyoto, Japan (1990) pp. 511–514.Google Scholar
13.Duda, R. O. and Hart, P. E., Pattern Classification and Scene Analysis. (Wiley-Interscience, New York, 1973).Google Scholar
14.Hongo, T., Arakawa, H., Sugimoto, G., Tange, K. and Yamamoto, Y., “An Automatic Guidance System of a Self-Controlled Vehicle” IEEE Trans. Industrial Electronics IE-34, No. 1, 5–10 (02, 1987).CrossRefGoogle Scholar
15.Johnston, A. R., Assefi, T. and Lai, J. Y., “Automated Vehicle Guidance Using Discrete Reference Markers” IEEE Trans. Vehicular Technology VT-28, No. 1, 95–106 (02, 1979).CrossRefGoogle Scholar
16.Ishikawa, S., Kikuchi, A. and Kato, K., “Visual Self-Location of a Mobile Robot” KACC, Seoul, Korea, 694–699 (1989).Google Scholar
17.Wolf, P. R., Elements of Photogrammetry. (McGraw-Hill, New York, 1974).Google Scholar
18.Craig, J. J., Introduction to Robotics: Mechanics & Control (Addison Wesley, Workingham, UK, 1986).Google Scholar