Preview

Giroskopiya i Navigatsiya

Advanced search

Навигация мобильного робота с использованием эллиптических траекторий и эффективного алгоритма обнаружения препятствий в режиме реального времени

Abstract

This paper deals with the problem of mobile robot navigation in cluttered environment. Adaptive elliptic trajectories are exploited for reactive obstacle avoidance using only position information and uncertain range data. The obstacle avoidance strategy used is based on the elliptic limit-cycle principle where each obstacle is surrounded by an ellipse. The ellipse parameters are computed online using a sequence of uncertain range data. An online heuristic method combined with the ex-tended Kalman filter (EKF) is used to compute the ellipse parameters. It is demonstrated that this process ensures that all range data are surrounded by a computed ellipse. Moreover, this paper proposes a single control law to the multicontroller architecture where a reactive obstacle avoidance algorithm is embedded. The proposed control law is based on the Kanayama control law; it is designed to im-prove the performance of the controllers. The stability of this control architecture is proved according to the Lyapunov synthesis. Simulations and experiments in different environments have been performed to demonstrate the efficiency and reliability of the proposed online navigation in cluttered environment.

About the Authors

Ж. Вилка
Институт Паскаля (г. Клермон-Ферран)
France


Л. Адуан
Институт Паскаля (г. Клермон-Ферран)
France


Ю. Мезуар
Институт Паскаля (г. Клермон-Ферран)
Russian Federation


References

1. Latombe, J.C., Robot Motion Planning, Kluwer Academic Publishers, Boston, MA, 1991.

2. Rimon, E. and Koditschek, D., Exact Robot Navigation Using Artificial Potential Fields, IEEE Transactions on Robotics and Automation, 1992, vol. 8, no. 5, pp. 501–518.

3. Fraichard, T., Trajectory Planning in a Dynamic Workspace: a ‘State-Time Space” Approach, Advanced Robotics, 1999, vol. 13, no. 1, pp. 75–94.

4. Jur-Van-Den, B., and Overmars, M., Roadmap-Based Motion Planning in Dynamic Environ-ments, IEEE Transactions on Robotics, 2005, vol. 21(5), pp. 885–897.

5. Egerstedt, M. and Hu, X., A Hybrid Control Approach to Action Coordination for Mobile Robots, Automatica, 2002, vol. 38(1), pp. 125–130.

6. Toibero, J., Carelli, R., and Kuchen, B., Switching Control of Mobile Robots for Autonomous Navigation in Unknown Environments, IEEE International Conference on Robotics and Automation, 2007, pp. 1974–1979.

7. Adouane, L., Hybrid and Safe Control Architecture for Mobile Robot Navigation, 9th Conference on Autonomous Robot Systems and Competitions, Portugal, May 2009.

8. Khatib, O., Real-Time Obstacle Avoidance for Manipulators and Mobile Robots, International Journal of Robotics Research, 1986, vol. 5, pp. 90–99.

9. Arkin, R. C., Motor Schema-based Mobile Robot Navigation, International Journal of Robotics Research, 1989, vol. 8, no. 4, pp. 92–112.

10. Zapata, R., Cacitti, A., and Lepinay, P., DVZ-Based Collision Avoidance Control of Non-holonomic Mobile Manipulators, JESA, European Journal of Automated Systems, 2004, vol. 38(5), pp. 559–588.

11. Arkin, R.C., Behavior-Based Robotics, MIT Press, 1998.

12. De Luca, A. and Oriolo, G., Local Incremental Planning for Nonholonomic Mobile Robots, IEEE International Conference on Robotics and Automation, May 1994, vol. 1, pp. 104–110.

13. Kim D.-H. and Kim, J.-H., A Real-Time Limit-Cycle Navigation Method for Fast Mobile Robots and its Application to Robot Soccer, Robotics and Autonomous Systems, 2003, vol. 42(1), pp. 17–30.

14. Jie, M.S., Baek, J.H., Hong, Y.S., and Lee, K.W., Real Time Obstacle Avoidance for Mobile Robot Using Limit-Cycle and Vector Field Method, Knowledge-Based Intelligent Information and Engineering Systems, October 2006.

15. Adouane, L., Orbital Obstacle Avoidance Algorithm for Reliable and On-Line Mobile Robot Navigation, 9th Conference on Autonomous Robot Systems and Competitions, May 2009, Portugal.

16. Adouane, L., Benzerrouk, A., and Martinet, P., Mobile Robot Navigation in Cluttered Environment Using Reactive Elliptic Trajectories, 18th IFAC World Congress, August 2011.

17. Benzerrouk, A., Adouane, L., and Martinet, P., Lyapunov Global Stability for a Reactive Mo-bile Robot Navigation in Presence of Obstacles,” ICRA’10 International Workshop on Robotics and Intelligent Transportation System, 2010.

18. Kanayama, Y., Kimura, Y., Miyazaki, F., and Noguchi, T., A Stable Tracking Control Method for an autonomous mobile robot, Proceedings of the IEEE International Conference on Robotics and Automation, May 1990, pp. 384 – 389.

19. Welzl, E., Smallest Enclosing Disks (Balls and Ellipsoids), Results and New Trends in Computer Science, Springer-Verlag, 1991, pp. 359–370.

20. Zhang, Z., Parameter Estimation Techniques: A Tutorial with Application to Conic Fitting, Image and Vision Computing, 1997, vol. 15, pp. 59–76.

21. Vilca, J., Adouane, L., and Mezouar, Y., On-Line Obstacle Detection Using Data Range for Reactive Obstacle Avoidance, 12th International Conference on Intelligent Autonomous Systems, Korea, June 2012.

22. Xiong, K., Wei, C., and Liu, L., Robust Kalman Filtering for Discrete-Time Nonlinear Systems with Parameter Uncertainties, Aerospace Science and Technology, 2011.

23. Fouque, C., Bonnifait, P., and Betaille, D., Enhancement of Global Vehicle Localization Using Navigable Road Maps and Dead-Reckoning, IEEE Position Location and Navigation Symposium, 2008.

24. Rigatos, G.G., Extended Kalman and Particle Filtering for Sensor Fusion in Motion Control of Mobile Robots, Mathematics and Computers in Simulation, November 2010, vol. 81, no. 3, pp. 590–607.

25. Levinson, J. and Thrun, S., Robust Vehicle Localization in Urban Environments Using Probabilistic Maps, IEEE International Conference on Robotics and Automation, Alaska, USA, May 2010.

26. Porrill, J., Fitting Ellipses and Predicting Confidence Envelopes Using a Bias Corrected Kalman Filter, Image and Vision Computing, February 1990, vol. 8, no. 1, pp. 37–41.

27. Vilca, J., Adouane, L., and Mezouar, Y., Robust Online Obstacle Detection Using Range Data for Reactive Navigation, 10th International IFAC Symposium on Robot Control, Croatia, September 2012.

28. Brooks, R.A., A Robust Layered Control System for a Mobile Robot, IEEE Journal of Robotics and Automation, vol. RA-2, March 1986, pp. 14–23.

29. Adouane, L. and Le Fort-Piat, N., Behavioral and Distributed Control Architecture of Control for Minimalist Mobile Robots, Journal Europen des Systèmes Automatisés, 2006, vol. 40, no. 2, pp. 177–196.

30. Maalouf, E., Saad, M., and Saliah, H., A Higher Level Path Tracking Controller for a Four-Wheel Differentially Steered Mobile Robot, Robotics and Autonomous Systems, 2006, vol. 54, pp. 23–33.

31. De Maesschalck, R., Jouan-Rimbaud, D., and Massart, D., The Mahalanobis Distance, Chemometrics and Intelligent Laboratory Systems, 2000, vol. 50, no. 1, pp. 1–18.

32. Barshan, B. and Kuc, R., Active Sonar for Obstacle Localization Using Envelope Shape Information, International Conference on Acoustics, Speech, and Signal Processing, April 1991, vol. 2, pp. 1273–1276.

33. Burguera, A., Gonzlez, Y., and Oliver, G., Sonar Sensor Models and Their Application to Mo-bile Robot Localization, Sensors, December 2009, vol. 9, no. 12, pp. 10217–10243.

34. Khalil, H.K., Nonlinear Systems, 3rd ed., P. Hall, Ed., 2002.


Review

For citations:


 ,  ,   . Giroskopiya i Navigatsiya. 2012;20(4):71-92. (In Russ.)

Views: 20

JATS XML


Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.


ISSN 0869-7035 (Print)
ISSN 2075-0927 (Online)