A Lane Based Obstacle Avoidance Method for Mobile Robot Navigation

  • Ko, Nak-Yong (Department Information, Control, and Instrumentation Engineering and Factory Automation Center for parts of Vehicles, Chosun University) ;
  • Reid G. Simmons (School of Computer Science, Carnegie Mellon University) ;
  • Kim, Koung-Suk (Department Mechanical Information Engineering, Chosun University)
  • 발행 : 2003.11.01

초록

This paper presents a new local obstacle avoidance method for indoor mobile robots. The method uses a new directional approach called the Lane Method. The Lane Method is combined with a velocity space method i.e., the Curvature-Velocity Method to form the Lane-Curvature Method (LCM). The Lane Method divides the work area into lanes, and then chooses the best lane to follow to optimize travel along a desired goal heading. A local heading is then calculated for entering and following the best lane, and CVM uses this local heading to determine the optimal translational and rotational velocities, considering some physical limitations and environmental constraint. By combining both the directional and velocity space methods, LCM yields safe collision-free motion as well as smooth motion taking the physical limitations of the robot motion into account.

키워드

참고문헌

  1. J. Borenstein and Y. Koren, 'The vector field histogram-fast obstacle avoidance for mobile robots', IEEE Trans. on Robotics and Automation, no. 3, pp. 278-298, 1991 https://doi.org/10.1109/70.88137
  2. Buhmann, J., Burgard, W., Cremers, A. B., Fox, D., Hofmann, T., Schneider, F., Strikos, J. and Thurn, S., 1995, 'The mobile robot Rhino,' AI Magazine, Vol. 16, No. 2, pp. 278-288
  3. David Kortenkamp, Marcus Huber, Charles Cohen, Ulich Raschke, Frank Koss, and Clare Congdon, 1998, 'Integrating High-Speed Obstacle Avoidance, Global Path Planning and Vision Sensing on a Mobile Robot,' in Artificial Intelligence and Mobile Robots edited by David Kortenkamp, R. Peter Bonasso and Robin Murphy, MIT Press, pp. 53-71
  4. Feiten, W., Bauer, R. and Lawitzky, G., 1994, 'Robust Obstacle Avoidance in Unknown and Cramped Environment,' In Proc. IEEE Int. Conf. Robotics and Automation, pp. 2412-2417 https://doi.org/10.1109/ROBOT.1994.351150
  5. Fox, D., Burgard, W. and Thrun, S., 1995, 'The Dynamic Window Approach to Collision Avoidance,' Tech Report IAI-TR-95-13, CS department, University of Bonn
  6. Hwang, Y. K. and Ahuja, N., 1992, 'A Potential Field Approach to Path Planning,' IEEE Trans. on Robotics and Automation, Vol. 8, No. 1, pp. 23-32 https://doi.org/10.1109/70.127236
  7. Hye-Kyung Cho, Young-Jo Cho and Bum-Jae You, 2001, 'Integration of Schma-Based Behavior and Variable-Resolution Cognitive Maps for Stable Indoor Navigation,' Proc. IEEE International Conference on Robotics and Automation, pp. 3618-3623, Seoul, Korea https://doi.org/10.1109/ROBOT.2001.933179
  8. Ihn, N. G., 1996, 'A Global Collision-Free Path Planning Using Parametric Parabola Through Geometry Mapping of Obstacles in Robot Work Space,' KSME International Journal, Vol. 10, No. 4, pp. 443-449 https://doi.org/10.1007/BF02942780
  9. Jacobs, P. and Canny, J., 1989, 'Planning Smooth Paths for Mobile Robots,' In Proc. IEEE Int. Conf on Robotics and Automation, Scottsdale AZ, pp. 2-7 https://doi.org/10.1109/ROBOT.1989.99959
  10. Kang, S. K. and Lim, J. H., 1999, 'Sonar Based Position Estimation System for an Autonomous Mobile Robot Operating in an Unknown Environment,' KSME International Journal, Vol. 13, No. 4, pp. 339-349 https://doi.org/10.1007/BF02939322
  11. Kant, K. and Zucker, S. W., 1986, 'Toward Efficient Trajectory Planning: The Path-Velocity Decomposition,' The Int. Journal of Robotics Research, Vol. 5. No. 3, pp. 72-89 https://doi.org/10.1177/027836498600500304
  12. Kelly, A., 1995, 'An Intelligent Predictive Control Approach to the High Speed Cross Country Autonomous Navigation Problem,' Tech Report CMU-CS-TR-95-33, School of Computer Science, Carnegie Mellon University
  13. Khatib, O., 1986, 'Real Time Obstacle Avoidance for Manipulators and Mobile Robots,' International Journal of Robotics Research, Vol. 5, No. 1, pp. 90-96 https://doi.org/10.1177/027836498600500106
  14. Latombe, J. C., 1991, 'Robot motion planning,' Kluwer Academic Publishers
  15. Louste, C. and Liegeois, A., 2002, 'Path Planning for Non-Holonomic Vehicles: A Potential Viscous Fluid Field Method,' Robotica, Vol. 20, No. 3, pp. 291-298 https://doi.org/10.1017/S0263574701003691
  16. Simmons, R. G., 1996, 'The Curvature-Velocity Method for Local Obstacle A voidance,' IEEE International Conference on Robotics and Automation, Minneapolis MN https://doi.org/10.1109/ROBOT.1996.511023
  17. Simmons, R., Goodwin, R., Zita Haigh, K., Koening, S. and O'Sullivan, J., 1997, 'A Layered Architecture for Office Delivery Robots,' Proc. Autonomous Agents '97, pp. 245-252, Marina del Rey, CA.
  18. Tai Hun Kwon, 1997, 'A Collision-Free Path Planning Using Linear Parametric Curve Based on Geometry Mapping of Obstacles,' Transactions of KSME A, Vol. 21, No. 12, pp. 1992-2007
  19. Wilson D. Esquivel and Luciano E. Chiang, 2002, 'Nonholonomic Path Planning Among Obstacles Subject to Curvature Restrictions,' Robotica, Vol. 20. No. 1, pp. 49-58 https://doi.org/10.1017/S0263574701003630