In this paper we present a novel feature initialization technique for the Simultaneous Localization and Mapping (SLAM) algorithm. The initialization scheme extends previous approaches for identifying new confirmed features and is shown to improve the steady-state performance of the filter by incorporating tentative features into the filter as soon as they are observed. Constraints are then applied between multiple feature estimates when a feature is confirmed. Observations that are subsequently deemed as spurious are removed from the state vector after an appropriate timeout. It is shown that information that would otherwise be lost can therefore be used consistently in the filter. Results of this algorithm applied to data collected using a submersible vehicle are also shown.
Get full access to this article
View all access options for this article.
References
1.
Ayache, N., and Faugeras, O. 1989. Maintaining a representation of the environment of a mobile robot . IEEE Transactions on Robotics and Automation5(6): 804-819 .
2.
Brooks, R. A. 1986. A robust, layered control system for a mobile robot . IEEE Transactions on Robotics and Automation2(1): 14-23 .
3.
Castellanos, J. A., Montiel, J. M. M., Neira, J., and Tardos, J. D. 1999. The SpMap: A probabilistic framework for simultaneous localization and map building . IEEE Transactions on Robotics and Automation15(5): 948-952 .
4.
Castellanos, J. A., Montiel, J. M. M., Neira, J., and Tardos, J. D. 2000. Sensor influence in the performance of simultaneous mobile robot localization and map building. In P. Corke and J. Trevelyan, eds., Experimental Robotics IV, Springer-Verlag, Berlin , pp. 287-296.
5.
Csorba, M. 1997. Simultaneous Localization and Map Building. PhD Thesis, University of Oxford.
6.
Deans, M. C. 2002. Maximally informative statistics for localization and mapping . In Proceedings of the IEEE International Conference on Robotics and Automation, Vol. 2, pp. 1824-1829 .
7.
Dissanayake, M. W. M. G., Newman, P., Durrant-Whyte, H. F., Clark, S., and Csorba, M. 2000. An experimental and theoretical investigation into simultaneous localization and map building. Experimental Robotics IV, pp. 265-274.
8.
Dissanayake, M. W. M. G., Newman, P., Clark, S., Durrant-Whyte, H. F., and Csobra, M. June 2001. A solution to the simultaneous localization and map building (slam) problem . IEEE Transactions on Robotics and Automation17(3): 229-241 .
9.
Durrant-Whyte, H. F. 2001. Introduction to Estimation and the Kalman Filter, Australian Centre for Field Robotics .
10.
Feder, H. J. S. 1999. Simultaneous Stochastic Mapping and Localization. PhD Thesis, Massachusetts Institute of Technology, Department of Mechanical Engineering.
11.
Feder, H. J. S., Leonard, J. J., and Smith, C. M. 1999. Adaptive mobile robot navigation and mapping . International Journal of Robotics Research (Special Issue on Field and Service Robotics) 18(7): 650-668 .
12.
Gelb, A. 1996. Applied Optimal Estimation, 14th edn, MIT Press .
13.
Guivant, J., Nebot, E. M., and Durrant-Whyte, H. F. 2000. Simultaneous localization and map building using natural features in outdoor environments . In Proceedings of the 6th International Conference on Intelligent Autonomous Systems, Vol. 1, pp. 581-588 .
14.
Gutmann, J. S., and Konolige, K. 2000. Incremental mapping of large cyclic environments . In Proceedings of the IEEE International Symposium on Computational Intelligence in Robotics and Automation, pp. 318-325 .
15.
Kuipers, B. J., and Byun, Y. T. 1991. A robot exploration and mapping strategy based on a semantic hierarchy of spatial representations . Robotics and Autonomous Systems8(1-2): 47-63 .
16.
Leonard, J. J., and Durrant-Whyte, H. F. 1991. Simultaneous map building and localization for an autonomous mobile robot . In IEEE/RSJ International Workshop on Intelligent Robots and Systems, Vol. 3, pp. 1442-1447 .
17.
Leonard, J. J., and Durrant-Whyte, H. F. 1992. Directed Sonar Sensing for Mobile Robot Navigation, Kluwer Academic, Dordrecht .
18.
Leonard, J. J., and Feder, H. J. S. 1999. A computationally efficient method for large-scale concurrent mapping and localization . In Proceedings of the 9th International Symposium on Robotics Research, International Foundation of Robotics Research, pp. 169-176 .
19.
Levitt, T. S., and Lawton, D. T. 1990. Qualitative navigation for mobile robots . Artificial Intelligence Journal44(3): 305-360 .
20.
Lu, F., and Milios, E. 1997. Robot pose estimation in unknown environments by matching 2D range scans . Journal of Intelligent and Robotic Systems18(3): 249-275 .
21.
Majumder, S. 2001. Sensor Fusion and Feature Based Navigation for Subsea Robotics. PhD Thesis, University of Sydney, Australian Centre for Field Robotics.
22.
Majumder, S., Scheding, S., and Durrant-Whyte, H. F. 2000. Sensor fusion and map building for underwater navigation . In Proceedings of the Australian Conference on Robotics and Automation, Australian Robotics Association, pp. 25-30 .
23.
Maybeck, P. 1982. Stochastic Models Estimation and Control, Vol. 1, Academic, New York .
24.
Miller, K. S., and Leskiw, D. M. 1987. An Introduction to Kalman Filtering with Applications, 1st edn., Krieger Publishing Company .
25.
Montemerlo, M., Thrun, S., Koller, D., and Wegbreit, B. 2002. FastSLAM: A factored solution to the simultaneous localization and mapping problem . In Proceedings of the AAAI National Conference on Artificial Intelligence, Edmonton, Canada.
26.
Neira, J., and Tardos, J. 2001. Data association in stochastic mapping using the joint compatibility test . IEEE Transactions on Robotics and Automation17(6): 890-897 .
27.
Newman, P. 1999. On The Structure and Solution of the Simultaneous Localization and Map Building Problem. PhD Thesis, University of Sydney, Australian Centre for Field Robotics.
28.
Newman, P., and Durrant-Whyte, H. F. 1997. Toward terrain-aided navigation of a subsea vehicle. In A. Zelinsky, ed., Field and Service Robotics, Springer-Verlag, Berlin , pp. 231-236.
29.
Rencken, W. D. 1993. Concurrent localization and map building for mobile robots using ultrasonic sensors . In IEEE/RSJ International Workshop on Intelligent Robots and Systems, Vol. 3, pp. 2192-2197 .
30.
Rikoski, R. J., Leonard, J. J., and Newman, P. M. 2002. Stochastic mapping frameworks . In Proceedings of the IEEE International Conference on Robotics and Automation, Vol. 1, pp. 426-433 .
31.
Smith, R., Self, M., and Cheeseman, P. 1987. A stochastic map for uncertain spatial relationships . Autonomous Mobile Robots: Perception, Mapping and Navigation1: 323-330 .
32.
Smith, R., Self, M., and Cheeseman, P. 1990. Estimating uncertain spatial relationships in robotics. In G. T. Wilfong and I. J. Cox, eds., Autonomous Robot Vehicles, Springer-Verlag, Berlin , pp. 167-193.
33.
Smith, C., Feder, H., and Leonard, J. 1998. Multiple target tracking with navigation uncertainty . In Proceedings of the 37th IEEE International Conference on Decision and Control, Vol. 1, pp. 760-761 .
34.
and Autonomous Robots5(3-4): 253-271 (joint issue).
35.
Williams, S. B. 2001. Efficient Solutions to Autonomous Mapping and Navigation Problems. PhD Thesis, University of Sydney, Australian Centre for Field Robotics.
36.
Williams, S. B., Newman, P., Majumder, S., Rosenblatt, J., and Durrant-Whyte, H. F. 1999. Autonomous transect surveying of the great barrier reef . In Proceedings of the Australian Conference on Robotics and Automation, Australian Robotics Association, pp. 16-20 .
37.
Williams, S. B., Newman, P., Dissanayake, M. W. M. G., and Durrant-Whyte, H. F. 2000. Autonomous underwater simultaneous localization and mapping . In Proceedings of the IEEE International Conference on Robotics and Automation, Vol. 2, pp. 1793-1798 .
38.
Williams, S. B., Dissanayake, M. W. M. G., and Durrant-Whyte, H. F. 2001. Towards terrain-aided navigation for underwater robotics . Advanced Robotics15(5): 533-550 .
39.
Williams, S. B., Dissanayake, M. W. M. G., and Durrant-Whyte, H. F. 2002. An efficient approach to the simultaneous localization and mapping problem . In Proceedings of the IEEE International Conference on Robotics and Automation, Vol. 1, pp. 406-411 .
