Skip to main content Accessibility help
×
Home

Simultaneous landmark classification, localization and map building for an advanced sonar ring

  • Saeid Fazli (a1) and Lindsay Kleeman (a1)

Summary

An autonomous mobile robot operating in an unknown indoor environment often needs to map the environment while localizing within the map. Feature-based world models including line and point features are widely used by researchers. This paper presents a novel delayed-classi-fication algorithm to categorize these features using a recently developed high-performance sonar ring within a simultaneous localization and map-building (SLAM) process. The sonar ring sensor accurately measures range and bearing to multiple targets at near real-time repetition rates of 11.5 Hz to 6 m range, and uses 24 simultaneously fired transmitters, 48 receivers and multiple echoes per receiver. The proposed algorithm is based on hypothesis generation and verification using the advanced sonar ring data and an extended Kalman filter (EKF) approach. It is capable of initiating new geometric features and classifying them within a short distance of travel of about 10 cm. For each new sonar reading not matching an existing feature, we initiate a pair of probational line and point features resulting from accurate range and bearing measurements. Later measurements are used to confirm or remove the probational features using EKF validation gates. The odometry error model of the filter allows for variations in effective wheel separation required by pneumatic robot tyres. The implementation of the novel classification and SLAM algorithm is discussed in this paper and experimental results using real sonar data are presented.

Copyright

Corresponding author

*Corresponding author. E-mail: saeid.fazli@eng.monash.edu.au

References

Hide All
1.Kleeman, L., “Fast and accurate sonar trackers using double pulse coding,” Proceedings of the 1999 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'99): Human and Environment Friendly Robots with High Intelligence and Emotional Quotients, Kyongju, South Korea (Oct. 17–21, 1999) (IEEE, Piscataway, NJ) pp. 11851190.
2.Kuc, R. and Viard, V. B., “Physically based navigation strategy for sonar-guided vehicles,” Int. J. Robot. Res. 10, 7587 1991.
3.Murray, D. and Jennings, C., “Stereo vision based mapping and navigation for mobile robots,” Proceedings of the 1997 IEEE International Conference on Robotics and Automation (ICRA), Albuquerque, NM (Apr. 20–25, 1997) (IEEE, Piscataway, NJ) pp. 16941699.
4.Schroeter, C., Boehme, H.-J. and Gross, H.-M., “Robust map building for an autonomous robot using low-cost sensors,” Proceedings of the 2004 IEEE International Conference on Systems, Man and Cybernetics (SMC 2004), The Hague, The Netherlands (Oct. 10–13, 2004) (IEEE, New York) pp. 53985403.
5.Yata, T., Kleeman, L. and Yuta, S. I., “Fast-bearing measurement with a single ultrasonic transducer,” Int. J. Robot. Res. 17, 12021213 1998.
6.Davison, A., Mobile Robot Navigation Using Active Vision D. Phil. Thesis (Oxford, UK: University of Oxford, 1998.
7.Diosi, A. and Kleeman, L., “Advanced sonar and laser range finder fusion for simultaneous localization and mapping,” Proceedings of the 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Sendai, Japan (Sep. 28–Oct. 2, 2004) (IEEE, New York) pp. 18541859.
8.Li, M.-H., Hong, B.-R. and Luo, R.-H.,“Simultaneous localization and map building for mobile robot,” Harbin Gongye Daxue Xuebao/J. Harbin Inst. Technol. 36, 874876 2004.
9.Grossmann, A. and Poli, R., “Robust mobile robot localization from sparse and noisy proximity readings using Hough transform and probability grids,” Robot. Auton. Syst. 37, 118 2001.
10.Gartshore, R., Aguado, A. and Galambos, C., “Incremental map building using an occupancy grid for an autonomous monocular robot,” Proceedings of the 7th International Conference on Control, Automation, Robotics and Vision (ICARC), Singapore (Dec. 2–5, 2002) (Nanyang Technological University, Singapore) pp. 613618.
11.Leonard, J. J., Durrant-Whyte, H. F. and Cox, I. J., “Dynamic map building for an autonomous mobile robot,” Int. J. Robot. Res. 11, 286298 1992.
12.Maksarov, D. and Durrant-Whyte, H. F., “Mobile vehicle navigation in unknown environments: A multiple hypothesis approach,” IEE Proc. Control Theory Appl. 142, 385400 1995.
13.Tsubouchi, T., “Nowadays trends in map generation for mobile robots,” Proceedings of the 1996 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Osaka, Japan (Nov. 4–8, 1996) (IEEE, Piscataway, NJ) pp. 828833.
14.Song, K.-T. and Chang, C. C., “Ultrasonic sensor data fusion for environment recognition,” Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, Yokohama, Japan (Jul. 26–30, 1993) (IEEE, Piscataway, NJ) pp. 384390.
15.Chong, K. S. and Kleeman, L., “Feature-based mapping in real, large scale environments using an ultrasonic array,” Int. J. Robot. Res. 18, 319 1999.
16.Kleeman, L., “Advanced sonar and odometry error modeling for simultaneous localization and map building,” Proceedings of the 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems, Las Vegas, NV (Oct. 27–31, 2003) (IEEE, Piscataway, NJ) pp. 699704.
17.Leonard, J. J. and Durrant-Whyte, H. F., “Simultaneous map building and localization for an autonomous mobile robot,” Proceedings of the IEEE International Workshop on Intelligent Robots and Systems, Osaka, Japan (Nov. 1991) pp. 1442–1447.
18.Wijk, O. and Christensen, H. I., “Triangulation-based fusion of sonar data with application in robot pose tracking,” IEEE Trans. Robot. Autom. 16, 740752 2000.
19.Rencken, W. D., “Autonomous sonar navigation in indoor, unknown and unstructured environments,” Proceedings of the IEEE/RSJ/GI International Conference on Intelligent Robots and Systems, Munich, Germany (Sep. 12–16, 1994) (IEEE, Piscataway, NJ) pp. 431438.
20.Zunino, G. and Christensen, H. I., “Simultaneous localization and mapping in domestic environments,” Proceedings of the International Conference on Multisensor Fusion and Integration for Intelligent Systems, Baden-Baden, Germany (Aug. 20–22, 2001) (IEEE, Piscataway, NJ) pp. 6772.
21.Chong, K. S. and Kleeman, L., “Mobile-robot map building from an advanced sonar array and accurate odometry,” Int. J. Robot. Res. 18, 2036 1999.
22.Heale, A. and Kleeman, L., “A real time DSP sonar echo processor,” Proceedings of the 2000 IEEE/RSJ International Conference on Intelligent Robots and Systems, Takamatsu, Japan (Oct. 31–Nov. 5, 2000) (IEEE, Piscataway, NJ) pp. 12611266.
23.Jeon, H. J. and Kim, B. K., “Study on world map building for mobile robots with tri-aural ultrasonic sensor system,” Proceedings of the 1995 IEEE International Conference on Robotics and Automation, Nagoya, Japan (May 21–27, 1995) (IEEE, Piscataway, NJ) pp. 29072912.
24.Howell, J. and Donald, B. R., “Practical mobile robot self-localization,” Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), San Francisco, CA (Apr. 24–28, 2000) (IEEE, Piscataway, NJ) pp. 34853492.
25.Lorenzo, J. M. P., Vazquez-Martin, R., Nunez, P., Perez, E. J. and Sandoval, F., “A Hough-based method for concurrent mapping and localization in indoor environments,” Proceedings of the 2004 IEEE Conference on Robotics, Automation and Mechatronics, Singapore (Dec. 1–3, 2004) (IEEE, New York) pp. 840845.
26.Luo, R.-H. and Hong, B.-R., “Simultaneous localization and mapping based on multisensor fusion,” Harbin Gongye Daxue Xuebao/J. Harbin Inst. Technol. 36, 566569 2004.
27.Niblack, W. and Petkovic, D., “On improving the accuracy of the Hough transform,” Mach. Vis. Appl. 3, 87106 1990.
28.Yun, X., Latt, K. and Glennon, J. S., “Mobile robot localization using the Hough transform and neural networks,” Proceedings of the 1998 IEEE International Symposium on Intelligent Control, ISIC, Gaithersburg, MD (Sep. 1417, 1998) (IEEE, Piscataway, NJ) pp. 393400.
29.Fazli, S. and Kleeman, L., “Sensor design and signal processing for an advanced sonar ring,” Robotica, 24, 433446 2006.
30.Kleeman, L. and Kuc, R., “Mobile robot sonar for target localization and classification,” Int. J. Robot. Res. 14, 295318 1995.
31.Fazli, S. and Kleeman, L., “A low sample rate real time advanced sonar ring,” Proceedings of the 2004 Australasian Conference on Robotics and Automation, Canberra, Australia (Dec. 68 2004).
32.Fazli, S. and Kleeman, L., “A real time advanced sonar ring with simultaneous firing,” Proceedings of the 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems, Sendai, Japan (Sep. 28–Oct. 2, 2004) pp. 18721877.
33.Bar-Shalom, Y., Rong, X. Li and Kirubarajan, T., Estimation with Applications to Tracking and Navigation, [electronic resource] 1st ed. (Wiley-Interscience, New York, 2001.
34.Bosse, M., Newman, P., Leonard, J. and Teller, S., “Simultaneous localization and map building in large-scale cyclic environments using the atlas framework,” Int. J. Robot. Res. 23, 11131139 2004.
35.Kleeman, L. and Kuc, R., “Optimal sonar array for target localization and classification,” Proceedings of the 1994 IEEE International Conference on Robotics and Automation, San Diego, CA (May 8–13, 1994) (IEEE, Piscataway, NJ) pp. 31303135.

Keywords

Related content

Powered by UNSILO

Simultaneous landmark classification, localization and map building for an advanced sonar ring

  • Saeid Fazli (a1) and Lindsay Kleeman (a1)

Metrics

Full text views

Total number of HTML views: 0
Total number of PDF views: 0 *
Loading metrics...

Abstract views

Total abstract views: 0 *
Loading metrics...

* Views captured on Cambridge Core between <date>. This data will be updated every 24 hours.

Usage data cannot currently be displayed.