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4WS Unmanned Vehicle Lateral Control Using PUS and Gyro Coupled by Kalman Filtering

  • Lee, Kil-Soo (Graduate School of Mechanical Engineering, Pusan National University) ;
  • Park, Hyung-Gyu (Graduate School of Mechanical Engineering, Pusan National University) ;
  • Lee, Man-Hyung (Graduate School of Mechanical Engineering, Pusan National University)
  • Received : 2010.12.15
  • Accepted : 2011.02.07
  • Published : 2011.03.31

Abstract

The localization of vehicle is an important part of an unmanned vehicle control problem. Pseudolite ultrasonic system(PUS) is the method to find an absolute position with a high accuracy by using ultrasonic sensor. And Gyro is the inertial sensor to measure yaw angle of vehicle. PUS can be able to estimate the position of mobile robot precisely, in which errors are not accumulated. And Gyro is a more faster measure method than PUS. In this paper, we suggest a more accuracy method of calculating PUS which is numerical analysis approach named Newtonian method. And also propose the fusion method to increase the accuracy of estimated angle on moving vehicle by using PUS and Gyro integrated system by Kalman filtering. To control the 4WS unmanned vehicle, the trajectory following algorithm is suggested. And the new concept arbitration of goal controller is suggested. This method considers the desirability function of vehicle state. Finally, the performances of Newtonian method and designed controller were verified from the experimental results with the 4WS vehicle scaled 1/10.

Keywords

References

  1. Bender, J. G.(1991), “An overview of system studies of automated highway system”, IEEE Trans. On Vehicular Technology, Vol.40, No.1. https://doi.org/10.1109/25.69977
  2. Brown, R. G. and Hwang, P. Y. C.(1997), Introduction to random signals and applied Kalman filtering, 3rd ed., Wiley, New York.
  3. Ebken, J., Bruch, M., and Lum, J.(2005), “Applying unmanned ground vehicle technologies to unmanned surface vehicles”, International Society for Optical Engineering, Vol.5804, No.1, pp.585-596.
  4. Farrell, J. and Barth, M.(1998), The global positioning system & inertial navigation, McGraw-Hill, New York.
  5. Fulton, J. and Pransky, J.(2004), “DARPA Grand Challenge - a pioneering event for autonomous robotic ground vehicles”, The Industrial Robot, Vol.31, No.5, pp.414-422. https://doi.org/10.1108/01439910410551827
  6. Hall, C. S., Marsh, J. N., Scott, M. J., Gaffney, P. J., Wickline, S. A., and Lanza, G. M.(2001), “Temperature dependence of ultrasonic enhancement with a site-targeted contrast agent”, The Journal of the Acoustical Society of America, Vol.110, No.3,pp.1677-1684. https://doi.org/10.1121/1.1395584
  7. Hedrick, J. K., McMahon, D. H., and Swaroop, D.(1993), “Vehicle modeling and control for automated highway system”, ITS Publication.
  8. Kodaira, M., Ohtomo, T., Tanaka, A., Iwatsuki, M., and Ohuchi, T.(1996), “Obstacle avoidance travel control of robot vehicle using neural network”, Systems and Computers in Japan, Vol.27, No.12, pp.102-112. https://doi.org/10.1002/scj.4690271209
  9. Kim, S. Y.(2005), “Position estimation and performance evaluation of a mobile robot using ultrasonic pseudo-satellites”, Master Thesis, Pusan National University.
  10. Lovece, J.(1994), “Unmanned Vehicle Update: recent activities and trends relating to unmanned systems programs”, Unmanned Systems, Vol.12, No.1.
  11. Schoenian, R. J. and Cameron, D. L.(1996), “CVO vehicle-to-roadside communications applications”, SAE Transactions, Vol.104, No.2, pp.824-829.

Cited by

  1. Lateral controller design for an unmanned vehicle via Kalman filtering vol.13, pp.5, 2012, https://doi.org/10.1007/s12239-012-0080-x