Hostname: page-component-76fb5796d-5g6vh Total loading time: 0 Render date: 2024-04-26T19:13:12.868Z Has data issue: false hasContentIssue false
  • English
  • Français

Beacon selection and calibration for the efficient localization of a mobile robot

Published online by Cambridge University Press:  02 August 2013

Jaehyun Park  and
Jangmyung Lee
Jaehyun Park
Affiliation:
Department of Electrical Engineering, Pusan National University, Busan 609-735, South Korea
Jangmyung Lee*
Affiliation:
Department of Electrical Engineering, Pusan National University, Busan 609-735, South Korea
*
*Corresponding author. E-mail: jmlee@pusan.ac.kr; jangmlee@hanmail.net
Get access Rights & Permissions [Opens in a new window]

Summary

This paper proposes a localization scheme using ultrasonic beacons in an unstructured multi-block workspace. Indoor localization schemes using ultrasonic sensors have widely been studied due to their low costs and high accuracies. However, ultrasonic sensors are susceptible to environmental noise due to the propagation characteristics of ultrasonic waves. In addition, the decay of ultrasonic signals over long distances implies that ultrasonic sensors are unsuitable for use in large indoor environments. To overcome these shortcomings of ultrasonic sensors, while retaining their advantages, a multi-block approach was devised by dividing an indoor space into several blocks with multiple beacons in each block. However, it is difficult to divide an indoor space into several blocks when beacons cannot be installed in a regular manner or when some new beacons are installed. To resolve this difficulty, a dynamic algorithm is needed to divide an indoor space into multiple blocks and to select suitable beacons. Therefore, this paper proposes a real-time localization scheme to estimate the position of a mobile robot independent of beacon locations and to estimate the position of a new beacon installed at an unknown position. A beacon selection algorithm was developed to select optimal beacons according to robot position and to set up sets of beacons for mobile robot navigation. By using the new beacon searching and calibration algorithm, a mobile robot is able to navigate in an unknown space without requiring the additional setup time needed to install new beacons. The performance of the proposed localization system was verified using real experiments.

Keywords

Control of robotic systemsMobile robotsNavigationRobot localizationSensor networks
Type
Articles
Information
Robotica , Volume 32 , Issue 1 , January 2014 , pp. 115 - 131
Copyright
Copyright © Cambridge University Press 2013 

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.Myung, H., Lee, H. K., Choi, K. and Bang, S. W., “Mobile robot localization with gyroscope and constrained Kalman filter,” Int. J. Control Autom. Syst. 8 (3), 667–676 (2010).CrossRefGoogle Scholar
2.Borenstein, J. and Feng, L., “Measurement and correction of systematic odometry errors in mobile robots,” IEEE Trans. Robot. Autom. 12, 869–880 (1996).CrossRefGoogle Scholar
3.Tsai, C. C., “A localization system of a mobile robot by fusing dead-reckoning and ultrasonic measurements,” IEEE Trans. Ind. Electron. 47 (5), 1399–1404 (1998).Google Scholar
4.Abuhashim, T. S., Adbedl-Hagez, M. F. and Al-Jarrah, M. A., “Building a robust integrity monitoring algorithm for a low cost GPS-aided-INS system,” Int. J. Control Autom. Syst. 8 (5), 1108–1122 (2010).CrossRefGoogle Scholar
5.Amarasinghe, D., Mann, G. K. I. and Gosine, R. G., “Landmark detection and localization for mobile robot applications; a multisensor approach,” Robotica 28 (5), 663–673 (2010).CrossRefGoogle Scholar
6.Kwok, N. M., Ha, Q. P., Huang, S., Dissanayake, G. and Fang, G., “Mobile robot localization and mapping using a gaussian sum filter,” Int. J. Control Autom. Syst. 5 (3), 251–268 (2007).Google Scholar
7.Parra, I., Sotelo, M. A., Llorca, D. F. and Ocaña, M., “Robust visual odometry for vehicle localization in urban environments,” Robotica 28, 441–452 (2010).CrossRefGoogle Scholar
8.Han, S. S., Lim, H. S. and Lee, J. M. “An efficient localization scheme for a differential-driving mobile robot based on RFID system,” IEEE Trans. Ind. Electron. 54 (6), 1–8 (2007).CrossRefGoogle Scholar
9.Tsai, C. C., “A localization system of a mobile robot by fusing dead-reckoning and ultrasonic,” IEEE Trans. Instrum. Meas. 47, 1399–1404 (1998).CrossRefGoogle Scholar
10.Qinhe, W. and Hashimoto, H., “Fast Localization of Multi-Targets in the Intelligent Space,” Proceedings of the Annual Conference SICE, Tagawa, Japan (2007) pp. 264–269.Google Scholar
11.Seo, D. G. and Lee, J. M., “Localization Algorithm for a Mobile Robot Using iGS,” Proceedings of the 17th International Federation of Automatic Control World Congress, Seoul, Korea (2008) pp. 742–747.Google Scholar
12.Manolakis, D. E., “Efficient solution and performance analysis of 3D position estimation by trilateration,” IEEE Trans. Aerosp. Electron. Syst. 32, 1239–1248 (1996).CrossRefGoogle Scholar
13.Thomas, F. and Ros, L., “Revisiting trilateration for robot localization,” IEEE Trans. Robot. 21, 93–101 (2005).CrossRefGoogle Scholar
14.Barshan, B., “Fast processing techniques for accurate ultrasonic range measurements,” IOP J. Meas. Sci. Technol. 11, 45–50 (2000).CrossRefGoogle Scholar
15.Eom, W. S. and Lee, J. M., “Ubiquitous Positioning Network of a Mobile Robot with Active Beacon Sensors,” Proceedings of the International Conference on Circuits/System, Computers and Communications, Busan, Korea (2007) pp. 255–256.Google Scholar
16.Yi, S. Y. and Choi, B. W., “Autonomous navigation of indoor mobile robots using a global ultrasonic system,” Robotica 22, 369–374 (2004).CrossRefGoogle Scholar
17.Manolakis, D. E., “Efficient solution and performance analysis of 3-D position estimation by trilateration,” IEEE Trans. Aerosp. Electron. Syst. 32, 1239–1248 (1996).CrossRefGoogle Scholar
18.Kim, S. B., Lee, J. M. and Lee, I. O., “Precise Indoor Localization System For a Mobile Robot Using Auto Calibration Algorithm,” Proceedings of the 13th International Conference on Advanced Robotics, Jeju, Korea (2007) pp. 635–640.Google Scholar
19.Sun, T., Chen, L., Han, C. and Gerla, M., “Reliable Sensor Networks for Planet Exploration,” Proceedings of IEEE International Conference Networking, Sensing and Control, Tuscon AZ, USA (2005) pp. 816–821.Google Scholar
20.Nam, M. Y., Sabbagh, M. A., Kim, J. E., Yoon, M. K., Lee, C. G. and Ha, E. Y., “A real-time ubiquitous system for assisted living: Combined scheduling of sensing and communication for real-time tracking,” IEEE Trans. Comput. 57 (6), 795–808 (2008).CrossRefGoogle Scholar