International Journal of Automotive Technology

, Volume 18, Issue 6, pp 1099–1107 | Cite as

Application of iterative learning control in tracking a Dubin’s path in parallel parking

  • Benjamas Panomruttanarug


Intelligent parking assist systems will soon be available for most vehicles on the market. Many optimal parking trajectories and control strategies have been proposed for reverse parking. However, most of these require intensive computation, causing difficulties in practical use. This paper makes use of a classical path planning method to find the shortest parking path, and establishes the possibility of integrating iterative learning control (ILC) to exploit the capability of learning from experience to track the designed path. The effectiveness of the ILC structure is demonstrated by simulation and experiments. Tracking performance is shown to be much improved by using a simple learning control law.

Key words

Parallel parking Dubin’s path Iterative learning control Steering control 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Boer, G. A. D. and Albada, G. D. V. (1993). The MARIE autonomous mobile robots. Proc. Conf. Intelligent Autonomous Systems -IAS 3, 164–173.Google Scholar
  2. Brussel, H. V. and Schutter, J. D. (1991). Hierarchical control of free-navigation AGVs. Proc. Int. Workshop on Information Processing in Autonomous Mobile Robots, 105–119.CrossRefGoogle Scholar
  3. Chen, C.-Y. and Feng, H.-M. (2009). Hybrid intelligent vision-based car-like vehicle backing systems design. Expert Systems with Applications 36, 4, 7500–7509.CrossRefGoogle Scholar
  4. D’Andrea-Novel, B., Campion, G. and Bastin, G. (1995). Control of nonholonomic wheeled mobile robots by state feedback linearization. Int. J. Robotics Research 14, 6, 543–559.CrossRefzbMATHGoogle Scholar
  5. Daxwanger, W. A. and Schmidt, G. K. (1995). Skill-based visual parking control using neural and fuzzy networks. Proc. IEEE Int. Conf. System, Cybernetics, 2, 1659–1664.Google Scholar
  6. Delchev, K. (2013). Iterative learning control for robotic manipulators: A bounded-error algorithm. Int. J. Adaptive Control and Signal Processing 28, 12, 1454–1473.MathSciNetCrossRefzbMATHGoogle Scholar
  7. Dolgov, D., Thrun, S., Montemerlo, M. and Diebel, J. (2010). Path planning for autonomous vehicles in unknown semi-structured environments. Int. J. Robotics Research 29, 5, 485–501.CrossRefGoogle Scholar
  8. Dong, W. and Kuhnert, K.-D. (2005). Robust adaptive control of nonholonomic mobile robot with parameter and nonparameter uncertainties. IEEE Trans. Robotics 21, 2, 261–266.CrossRefGoogle Scholar
  9. Du, X. and Tan, K. K. (2015). Autonomous reverse parking system based on robust path generation and improved sliding mode control. IEEE Trans. Intelligent Transportation Systems 16, 3, 1225–1237.CrossRefGoogle Scholar
  10. Dubins, L. E. (1957). On curves of minimal length with a constraint on average curvature and with prescribed initial and terminal position and tangents. American J. Mathematics 79, 3, 497–516.MathSciNetCrossRefzbMATHGoogle Scholar
  11. Heinen, M. R., Osorio, F. S., Heinen, F. J. and Kelber, C. (2006). SEVA3D: Using articial neural networks to autonomous vehicle parking control. Neural Networks, IJCNN Int. Joint Conf., IEEE, 4704–4711.Google Scholar
  12. Jenkins, R. E. and Yuhas, B. P. (1993). A simplified neural network solution through problem decomposition: The case of the truck backer-upper. IEEE Trans. Neural Network 4, 4, 718–720.CrossRefGoogle Scholar
  13. Jiang, K. and Seneviratne, L. D. (1999). A sensor guided autonomous parking system for nonholonomic mobile robots. Proc. IEEE Int. Conf. Robotics and Automation, 311–316.Google Scholar
  14. Kanayama, Y. and Hartman, B. I. (1989). Smooth local path planning for autonomous vehicles. Proc. IEEE Int. Conf. Robotics and Automation, 1265–1270.Google Scholar
  15. Khoshnejad, M. and Demirli, K. (2005). Autonomous parallel parking of a car-like mobile robot by a neurofuzzy behavior-based controller. Annual Meeting of the North American Fuzzy Information Processing Society, 814–819.Google Scholar
  16. Kim, E., Kim, J. and Sunwoo, M. (2014). Model predictive control strategy for smooth path tracking of autonomous vehicles with steering actuator dynamics. Int. J. Automotive Technology 15, 7, 1155–1164.CrossRefGoogle Scholar
  17. Kong, S. G. and Kosko, B. (1990). Comparison of fuzzy and neural truck backer-upper control. IJCNN Int. Joint Conf. Neural Networks, 349–358.Google Scholar
  18. Lee, C.-K., Lin, C.-L. and Shiu, B.-M. (2009). Autonomous vehicle parking using hybrid artificial intelligent approach. J. Intelligent and Robotic Systems 56, 3, 319–343.CrossRefzbMATHGoogle Scholar
  19. Li, T.-H. S., Lee, M.-H., Lin, C.-W., Liou, G.-H. and Chen, W.-C. (2016). Design of autonomous and manual driving system for 4WIS4WID vehicle. IEEE Access, 4, 2256–2271.CrossRefGoogle Scholar
  20. Macek, K., Philippsen, R. and Siegwart, R. (2008). Path following for autonomous vehicle navigation with inherent safety and dynamics margin. IEEE Intelligent Vehicles Symp., 108–113.Google Scholar
  21. Naderi Samani, N., Ghaisari, J. and Danesh, M. (2016). Parallel parking of a car-like mobile robot based on the P-domain path tracking controllers. IET Control Theory & Applications 10, 5, 564–572.MathSciNetCrossRefGoogle Scholar
  22. Ngo, T., Nguyen, M. H., Wang, Y., Ge, J., Wei, S. and Mai, T. L. (2014). An adaptive iterative learning control for robot manipulator in task space. Int. J. Computers, Communications & Control (IJCCC) 7, 3, 518–529.CrossRefGoogle Scholar
  23. Oentaryo, R. J. and Pasquier, M. (2004). Self-trained automated parking system. 8th Control, Automation, Robotics and Vision Conf., 1005–1010.Google Scholar
  24. Panomruttanarug, B. and Higuchi, K. (2010). Fuzzy logic based autonomous parallel parking system with kalman filtering. SICE J. Control, Measurement, and System Integration 3, 4, 266–271.CrossRefGoogle Scholar
  25. Paromtchik, I. E. and Laugier, C. (1996). Motion generation and control for parking an autonomous vehicle. Proc. IEEE Int. Conf. Robotics and Automation, 3117–3122.CrossRefGoogle Scholar
  26. Stentz, A. (1997). Optimal and efficient path planning for partially known environments. Intelligent Unmanned Ground Vehicles, 203–220.CrossRefGoogle Scholar
  27. Vorashompoo, A., Panomruttanarug, B. and Higuchi, K. (2011). Bidirectional best first based autonomous parallel parking system. 8th Electrical Engineering Electronics, Computer, Telecommunications and Information Technology, 593–596.Google Scholar
  28. Vorobieva, H., Glaser, S., Minoiu-Enache, N. and Mammar, S. (2015). Automatic parallel parking in tiny spots: Path planning and control. IEEE Trans. Intelligent Transportation Systems 16, 1, 396–410.CrossRefGoogle Scholar
  29. Wang, Q., Wulfmeier, M. and Wagner, B. (2015). Voronoibased heuristic for nonholonomic search-based path planning. Advances in Intelligent Systems and Computing, 445–458.Google Scholar
  30. Wang, W., Song, Y., Zhang, J. and Deng, H. (2014). Automatic parking of vehicles: A review of literatures. Int. J. Automotive Technology 15, 6, 967–978.CrossRefGoogle Scholar
  31. Xu, J., Chen, G. and Xie, M. (2000). Vision-guided automatic parking for smart car. Proc. IEEE Int. Vehicles Symp., 725–730.Google Scholar
  32. Ye, Y. and Wang, D. (2006). Implementation of ILC batch update using a robotic experimental setup. Microprocessors and Microsystems 30, 5, 259–267.CrossRefGoogle Scholar
  33. Zhao, Y., Ding, F., Guo, L. and Yuan, Y. (2016). Navigation controller design using fuzzy logic theory for vehicle parallel automatic parking. J. Balkan Tribological Association 22, 2, 1289–1298.Google Scholar

Copyright information

© The Korean Society of Automotive Engineers and Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  1. 1.Department of Control System and Instrumentation EngineeringKing Mongkut’s University of Technology ThonburiBangkokThailand

Personalised recommendations