Hostname: page-component-77c89778f8-gvh9x Total loading time: 0 Render date: 2024-07-17T01:01:21.827Z Has data issue: false hasContentIssue false
  • English
  • Français

A three dimensional localiser for autonomous robot vehicles*

Published online by Cambridge University Press:  09 March 2009

Lindsay Kleeman
Lindsay Kleeman
Affiliation:
Intelligent Robotics Research Centre, Department of Electrical and Computer Systems Engineering, Monash University, Clayton VIC 3168, Australia
Get access Rights & Permissions [Opens in a new window]

Summary

A novel design of a three dimensional localiser intended for autonomous robot vehicles is presented. A prototype is implemented in air using ultrasonic beacons at known positions, and can be adapted to underwater environments where it has important applications, such as deep sea maintenance, data collection and reconnaissance tasks. The paper presents the hardware design, algorithms for position and orientation determination (six degrees of freedom), and performance results of a laboratory prototype. Two approaches are discussed for position and orientation determination – (i) fast single measurement set techniques and (ii) computationally slower Kalman filter based techniques. The Kalman filter approach allows the incorporation of robot motion information, more accurate beacon modelling and the capability of processing data from more than four beacons, the minimum number required for localisation.

Keywords

Position estimation3–D localisationKalman filteringUltrasonic navigationOrientationUnderwater vehicles
Type
Articles
Information
Robotica , Volume 13 , Issue 1 , January 1995 , pp. 87 - 94
Copyright
Copyright © Cambridge University Press 1995

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.Ifremer-irisa, R. V. and Lib-ubo, M. L., “Absolute location of underwater robot vehicles by acoustic data fusion”, IEEE International Conference on Robotics and Automation,Cincinnati, OhioMay 13–18 1990 pp. 1310–1315.Google Scholar
2.Yoerger, D. R. and Slotine, J. E., “Adaptive sliding control of an experimental underwater vehicle” IEEE International Conference on Robotics and Automation,Sacramento, California(April, 1991) pp. 2746–2751.Google Scholar
3.Leonard, J. J. and Bellingham, J. G., “Directed sensing strategies for feature-relative navigation” Sensor Fusion VI (SPIE Volume 2059), Boston MA, (09. 7, 1993) pp. 120–129.CrossRefGoogle Scholar
4.Bellingham, J. G., Consi, T. R., Tedrow, U. and Di Massa, Diane, “Hyperbolic acoustic navigation for underwater vehicles: implementation and demonstration”, IEEE AUV’92, Washington DC, (06, 1992) pp. 304–309.Google Scholar
5.Hallam, J., Forster, P. and Howe, J., “Map-free localization in a partially moving 3D world: the Edinburgh feature-based navigator” Proceedings of IAS-2,Amsterdam,(1988) pp. 726–736.Google Scholar
6.Kleeman, L., “Ultrasonic autonomous robot localization system”, IEEE International Conference Intelligent Robots and Systems ‘89Tsukuba, JAPAN(September, 1989) pp. 212–219.Google Scholar
7.Kleeman, L., “Optimal estimation of position and heading for mobile robots using ultrasonic beacons and deadreckoning” IEEE International Conference ‘on Robotics and Automation,Nice, France(May 10–15, 1992) pp. 2582–2587.Google Scholar
8.Kleeman, L., “Iterative algorithm for three dimensional autonomous robot localisation” Third National Conference on Robotics,Melbourne(June, 1990) pp. 210–219.Google Scholar
9.Kleeman, L., “A three dimensional localiser for autonomous robot vehicles” IEEE Region 10 Conference,Melbourne(November, 1992) pp. 860–864.Google Scholar
10.Frank, R. L., “Current developments in Loran-C” Proceedings of the IEEE 71, No. 10 (10 1983) pp. 1127–1139.CrossRefGoogle Scholar
11.Jazwinski, A. H., Stochastic Processes and Filtering Theory (Mathematics in Science and Engineering, Vol. 64) (Academic Press, New York, 1970).CrossRefGoogle Scholar
12.Leonard, J. F. & Durrant-Whyte, H. F., “Mobile robot localization by tracking geometric beacons” IEEE Transactions Robotics and Automation 7, No. 3, 376–382 (06, 1991).CrossRefGoogle Scholar
13.Rogers, D. F. and Adams, J. A., Mathematical Elements for Computer Graphics 2nd Edn (McGraw-Hill, New York, 1990).Google Scholar
14.Graig, J. J., Introduction to Robotics, Mechanics and Control (Addison-Wesley, Reading, 1989).Google Scholar
15.McKerrow, P. J.Introduction to Robotics (Addison-Wesley, Sydney, 1991).Google Scholar
16.Parilla, M., Anaya, J. J. and Fritsch, C., “Digital signal processing techniques for high accuracy ultrasonic range measurements” IEEE Trans, on Instrumentation and Measurement 40, No. 4, 759–763 (08, 1991).CrossRefGoogle Scholar
17.Marioli, D., Narduzzi, C., Offelli, C., Petri, D., Sardini, E. and Taroni, A., “Digital time-of-flight measurement for ultrasonic sensors” IEEE Trans, on Instrumentation and Measurement 41, No. 1, 93–97 (02, 1992).CrossRefGoogle Scholar
18.Poole, H. H., Fundamentals of Robotics Engineering (Van Nostrand Reinhold, New York, 1989).CrossRefGoogle Scholar