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Research Papers

Heading Estimation Based on Magnetic Markers for Intelligent Vehicles

[+] Author and Article Information
Yeun Sub Byun

Metropolitan Transportation Research Center,
Korea Railroad Research Institute,
#176 Cheoldobakmulkwan-ro, Uiwang-si,
Gyeonggi-do 16105, South Korea
e-mail: ysbyun@krri.re.kr

Young Chol Kim

Department of Electronics Engineering,
Chungbuk National University,
1 Chungdae-ro, Seowon-Gu, Cheongju,
Chungbuk 28644, South Korea
e-mail: yckim@cbu.ac.kr

1Corresponding author.

Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received May 6, 2015; final manuscript received March 4, 2016; published online May 13, 2016. Assoc. Editor: Beshah Ayalew.

J. Dyn. Sys., Meas., Control 138(7), 071009 (May 13, 2016) (8 pages) Paper No: DS-15-1205; doi: 10.1115/1.4033021 History: Received May 06, 2015; Revised March 04, 2016

This paper presents a new real-time heading estimation method for an all-wheel steered single-articulated autonomous vehicle guided by a magnetic marker system. To achieve good guidance control for the vehicle, precise estimation of the position and heading angle during travel is necessary. The main concept of this study is to estimate the heading angle from the relative orientations of the magnetic markers and the vehicle motion. To achieve this, a kinematic model of the all-wheel steered vehicle is derived and combined with the motion of a magnetic ruler mounted near each axle underneath the vehicle. The position coordinates and polarities of the magnetic markers, which are provided a priori, are used to determine the vehicle position at every detection instance. A gyroscope is employed to assist real-time heading estimation at sample times when there are no marker detection data. The proposed method was tested on a real vehicle and evaluated by comparing the experimental results with those of the differential global positioning system (DGPS) in real-time kinematics (RTK) mode. Experimental results show that the proposed method exhibits good performance for heading estimation.

Copyright © 2016 by ASME
Topics: Vehicles , Wheels
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References

Be, H. , 2006, “ Precise Navigation for a 4WS Mobile Robot,” J. Zhejiang Univ. Sci. A, 7(2), pp. 185–193. [CrossRef]
Abbott, E. , and Powell, D. , 1999, “ Land-Vehicle Navigation Using GPS,” Proc. IEEE, 87(1), pp. 145–162. [CrossRef]
Mayhew, D. M. , 1999, “ Multi-Rate Sensor Fusion for GPS Navigation Using Kalman Filtering,” M.Sc. Report, Virginia Polytechnic Institute, Blacksburg, VA.
Bonnifait, P. , Bouron, P. , Crubille, P. , and Meizel, D. , 2001, “ Data Fusion of Four ABS Sensors and GPS for an Enhanced Localization of Car-Like Vehicles,” IEEE International Conference on Robotics and Automation (ICRA), Seoul, Korea, May 21–26, pp. 1597–1602.
Jo, K. , Chu, K. , and Sunwoo, M. , 2012, “ Interacting Multiple Filter-Based Sensor Fusion of GPS With In-Vehicle Sensors for Real-Time Vehicle Position,” IEEE Trans. Intell. Transp. Syst., 13(1), pp. 329–343. [CrossRef]
Broggi, A. , Bertozzi, M. , Fascioli, A. , Lo Bianco, C. G. , and Piazzi, A. , 1999, “ The ARGO Autonomous Vehicle's Vision and Control Systems,” Int. J. Intell. Control Syst., 3(4), pp. 409–441.
Reina, G. , and Milella, A. , 2011, “ FLane: An Adaptive Fuzzy Logic Lane Tracking System for Driver Assistance,” ASME J. Dyn. Syst., Meas., Control, 133(2), p. 021002. [CrossRef]
Se, S. , Lowe, D. , and Little, J. , 2001, “ Vision-Based Mobile Robot Localization and Mapping Using Scale-Invariant Features,” IEEE International Conference on Robotics and Automation (ICRA), Seoul, Korea, May 21–26, pp. 2051–2058.
Randeniya, D. I. B. , Sarkar, S. , and Gunaratne, M. , 2010, “ Vision–IMU Integration Using a Slow-Frame-Rate Monocular Vision System in an Actual Roadway Setting,” IEEE Trans. Intell. Transp. Syst., 11(2), pp. 256–266. [CrossRef]
Bai, L. , and Wang, Y. , 2010, “ A Sensor Fusion Framework Using Multiple Particle Filters for Video-Based Navigation,” IEEE Trans. Intell. Transp. Syst., 11(2), pp. 348–358. [CrossRef]
Farrell, J. A. , Tan, H.-S. , and Yang, Y. , 2003, “ Carrier Phase GPS-Aided INS Based Vehicle Lateral Control,” ASME J. Dyn. Syst., Meas., Control, 125(3), pp. 339–353. [CrossRef]
Tan, H.-S. , Bougler, B. , Farrell, J. A. , and Yang, Y. , 2003, “ Automatic Vehicle Steering Controls: DGPS/INS and Magnetic Markers,” American Control Conference (ACC), Denver, CO, June 4–6, Vol. 1, pp. 60–65.
Farrell, J. , Barth, M. , Galijan, R. , and Sinko, J. , 1998, “ GPS/INS Based Lateral and Longitudinal Control Demonstration: Final Report,” California PATH Research Report, ITS, University of California, Berkeley, CA, Report No. UCB-ITS-PRR-98-28.
Minnesota Department of Transportation, 2001, “ Detailed Design, Intelligent Vehicle Initiative, Specialty Vehicle Field Operational Test,” Mn/DOT-US DOT Cooperative Agreement No. DTFH61-99-X-00101.
Minnesota Department of Transportation, 2002, “ Validation Report, Intelligent Vehicle Initiative, Specialty Vehicle Field Operational Test,” Mn/DOT-US DOT Cooperative Agreement No. DTFH61-99-X-00101.
Donath, M. , Shankwitz, C. , Alexander, L. , Gorjestani, A. , Cheng, P. , and Newstrom, B. , 2003, “ Bus Rapid Transit Lane Assist Technology Systems. Volume 1: Technology Assessment,” University of Minnesota, ITS Institute, Minneapolis, MN, Paper No. FTA-MN-26-7003.
Kim, E. , Darido, G. , and Schneck, D. , 2005, “ Las Vegas Metropolitan Area Express (MAX) BRT Demonstration Project Evaluation,” Federal Transit Administration, Washington, DC, Paper No. FTA VA-26-7222-2005.1.
Conde Bento, L. , and Nunes, U. , 2004, “ Autonomous Navigation Control With Magnetic Markers Guidance of a Cybernetic Car Using Fuzzy Logic,” Mach. Intell. Rob. Control Cyber Sci., 6(1), pp. 1–10.
Barata, M. , Nunes, U. , Conde Bento, L. , and Mendes, A. , 2004, “ Data Fusion of Wheel Encoders and Magnetic Sensors for Autonomous Vehicles Navigation,” 6th Portuguese Conference on Automatic Control (CONTROLO 2004), Faro, Portugal, June 7–9, pp. 31–37.
Xu, H. G. , Wang, C. , Yang, R. , and Yang, M. , 2006, “ Extended Kalman Filter Based Magnetic Guidance for Intelligent Vehicles,” IEEE Intelligent Vehicles Symposium, Tokyo, Japan, June 13–15, pp. 169–175.
Bourny, V. , Capitaine, T. , Barrandon, L. , Pegard, C. , and Lorthois, A. , 2001, “ A Localization System Based on Buried Magnets and Dead Reckoning for Mobile Robots,” IEEE International Symposium on Industrial Electronics (ISIE 2010), Bari, Italy, July 4–7, pp. 373–378.
Surrécio, A. , Nunes, U. , and Araújo, R. , 2005, “ Fusion of Odometry With Magnetic Sensors Using Kalman Filters and Augmented System Models for Mobile Robot Navigation,” IEEE International Symposium on Industrial Electronics (ISIE 2005), Dubrovnik, Croatia, June 20–23, pp. 1551–1556.
Lopes, A. C. , Moita, F. , Nunes, U. , and Solea, R. , 2007, “ An Outdoor Guidepath Navigation System for AMRs Based on Robust Detection of Magnetic Markers,” 12th IEEE Conference on Emerging Technologies and Factory Automation (ETFA 2007), Patras, Greece, Sept. 25–28, pp. 989–996.
Tan, H. , and Bougler, B. , 2001, “ Vehicle Lateral Warning, Guidance and Control Based on Magnetic Markers: PATH Report of AHSRA Smart Cruise 21 Proving Tests,” California PATH Program, Institute of Transportation Studies, University of California, Berkeley, CA, Paper No. UCB-ITS-PWP-2001-6.
Ryoo, Y. , and Park, J. , 2012, “ Design and Development of Magnetic Position Sensor for Magnetic Guidance System of Automated Ground Vehicle,” 12th International Conference on Control, Automation and Systems (ICCAS), Jeju Island, Korea, Oct. 17–21, pp. 988–991.
Frog, 2015, Frog AGV Systems, Utrecht, The Netherlands, http://www.frog.nl

Figures

Grahic Jump Location
Fig. 2

Sensors installed in the test vehicle

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Fig. 3

Magnetic ruler mounted underneath the test vehicle

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Fig. 4

Structure of the magnetic ruler (yms = 0): measurement origin of the magnetic sensor

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Fig. 5

Schematic of marker detection

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Fig. 6

Concept of heading angle estimation

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Fig. 7

Geometric relationships for the heading angle and ruler motion

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Fig. 8

Kinematic model of ruler motion

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Fig. 10

Locations of all magnetic markers and the markers detected during the test run

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Fig. 11

Comparison of heading angles

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Fig. 12

DGPS and estimated heading

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Fig. 13

Gyroscope angle during eight test laps and drift

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Fig. 14

Differences between the proposed heading estimation results and the gyroscope results during eight test laps

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Fig. 15

Steering angles of four wheels during eight test laps

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Fig. 16

Velocities of four wheels during eight test laps

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