대한기계학회논문집A (Transactions of the Korean Society of Mechanical Engineers A)

  • 제34권8호
  • /
  • Pages.971-980
  • /
  • 2010
  • /
  • 1226-4873(pISSN)
  • /
  • 2288-5226(eISSN)
대한기계학회 (The Korean Society of Mechanical Engineers)
권호 표지
DOI QR코드

DOI QR Code

D* 서치와 퍼지 알고리즘을 이용한 모바일 로봇의 충돌회피 주행제어 알고리즘 설계

Development of a Navigation Control Algorithm for Mobile Robots Using D* Search and Fuzzy Algorithm

  • 정윤하 (STX 조선해양 조선해양연구소) ;
  • 박효운 (윙쉽테크놀러지(주) 선형항법팀) ;
  • 이상진 (충남대학교 메카트로닉스공학과) ;
  • 원문철 (충남대학교 메카트로닉스공학과)
  • Jung, Yun-Ha (Shipbuilding & Ocean Research Institute, STX Offshore & Shipbuilding) ;
  • Park, Hyo-Woon (Hull & Navigation Team, Wing Ship Technology Co.) ;
  • Lee, Sang-Jin (Mechatronics Engineering, Chungnam Nat'l Univ.) ;
  • Won, Moon-Cheol (Mechatronics Engineering, Chungnam Nat'l Univ.)
  • 투고 : 2009.08.17
  • 심사 : 2010.06.18
  • 발행 : 2010.08.01
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

이 논문은 모바일 로봇이 고정 장애물 또는 움직이는 장애물이 존재하는 환경에서 장애물을 회피하며 운행될 수 있는 제어 알고리즘을 연구하였다. 이 제어 알고리즘은 $D^*$ 알고리즘과, 충돌 위험도 퍼지로직, 이동로봇의 행동결정 퍼지로직을 사용하여 전역경로계획과 지역경로계획을 수행한다. $D^*$ 알고리즘에는 로봇이 이동하는 2 차원 공간을 정방형 격자 분활하여 적용한다. 이 알고리즘은 파이썬 프로그래밍 언어와 이동로봇의 운동방정식을 사용한 시뮬레이션을 통해 검증하였다. 시뮬레이션 결과를 통해 알고리즘을 적용하여 로봇이 이동하는 장애물을 피하거나 모르는 고정 장애물을 피하면서 원하는 위치로 이동하는 것을 볼 수 있다.

In this paper, we present a navigation control algorithm for mobile robots that move in environments having static and moving obstacles. The algorithm includes a global and a local path-planning algorithm that uses $D^*$ search algorithm, a fuzzy logic for determining the immediate level of danger due to collision, and a fuzzy logic for evaluating the required wheel velocities of the mobile robot. To apply the $D^*$ search algorithm, the two-dimensional space that the robot moves in is decomposed into small rectangular cells. The algorithm is verified by performing simulations using the Python programming language as well as by using the dynamic equations for a two-wheeled mobile robot. The simulation results show that the algorithm can be used to move the robot successfully to reach the goal position, while avoiding moving and unknown static obstacles.

키워드

참고문헌

  1. Khatib, O., Spring 1986, "Real-Time Obstacle Avoidance for manipulator and Mobile Robots," The International Journal of Robotic Research, MIT Press, Cambridge, pp. 90-98.
  2. Rimon, E. and Koditschek, E. E., October 1992, "Exact Robot Navigation Using Artificial Potential Functions,” IEEE Transactions on Robotics and Automation, Vol. 8, No. 5.
  3. Yoo, H. I. and Kang, B. S., 2008, "Precise Motion Control of a Mobile Robot Based on Potential Field Method,” The KSME 2008 Dynamics and Control spring annual meeting, pp.177-180
  4. Park, M. G. and Lee, M. C., 2003, "A New Technique to Escape Local Minimum in Artificial Potential Field Based Path Planning,” KSME International Journal, Vol.17, No.12, pp. 1876-1885
  5. Park, M. G. and Lee, M. C., 2003, "A New Technique to Escape Local Minimum in Artificial Potential Field Based Path Planning,” KSME International Journal, Vol.17, No.12, pp. 1876-1885
  6. Qu, Y.-H. Pan, Q. and Yan, J.-G., Nov., 2005, “Flight Path Planning of UAV Based on Heuristically Search and Genetic Algorithms,” Industrial Electronics Society, 2005. IECON 2005. 31st Annual Conference of IEEE, Volume , Issue , 6-10.
  7. Bruce, J. and Veloso, M., October 2002, " Real-Time Randomized Path Planning for Robot Navigation,” Proc. of the 2002 IEEE/RSJ Int. Conference on Intelligent Robots and Systems EPFL, Lausanne, Switzerland, pp. 2383-2388.
  8. Konolige, K., 2000, "A Gradient Method for Realtime Robot Control,” Proc. of International Conf. on Intelligent Robots and Systems, pp. 639-646.
  9. Borenstein, J. and Koren, Y., June 1991, "The Vector Field Histogram - Fast Obstacle Avoidance for mobile Robots,” IEEE Journal of Robotics and Automation Vol. 7, No 3, pp. 278-288. https://doi.org/10.1109/70.88137
  10. Simmons, R., 1996, "The Curvature-Velocity Method for Local Obstacle Avoidance,” Proc. of International Conf. on Robotics and Automation.
  11. Kim, H. J., Shim, D. H. and Sastry, S., 2002, "Nonlinear Model Predictive Tracking Control for Rotorcraft-Based Unmanned Aerial Vehicles,” Proceedings of the American Control Conference, Anchorage, AK May 8-10.
  12. Ogren, P. and Leonard, N. E., 2003, "A Convergent Dynamic Window Approach to Obstacle Avoidance,” IEEE Transactions on Robotics and Automation,.
  13. Stachniss, C. and Burgard, W., October 2002, "An Integrated Approach to Goal-Directed Obstacle Avoidance Under Dynamic Constraints for Dynamic Environments,” Proceedings of the 2002 IEEE/RSJ, intl, Conference on Intelligent Robots and Systems EPFL, Lausanne, Switzerland.
  14. Fox, D., Burgard, W. and Thrun, S., 1997, "The Dynamic Window Approach to Collision Avoidance,” IEEE Robotics and Automation, Vol. 4, No. 1.
  15. Daios, E. P. and Maravillas O. A., Jr., 2002, "Cooperative Mobile Robots with Obstacle and Collision Avoidance Using Fuzzy Logic,” Proc. of the 2002 IEEE International Symposium on Intelligent Control, Vancouver, Canada, October 27-30, pp. 75-80.
  16. Russell, S. and Norvig, P., 2003, "Artificial Intelligence A Modern Approach," 2nd Ed. Prentice Hall.
  17. Stentz, A., 1994, "Optimal and Efficient Path Planning for Partially-known Environments,” Proceedings of the IEEE International Conference on Robotics and Automation, ICRA '94, Vol. 4, May, pp. 3310-3317.
  18. Aurenhammer, F. and Diagrams, V., 1991, “A Survey of a Fundamental Geometric Data Structure.” ACM Computing Surveys, Vol. 23, No. 3, pp. 345-405. https://doi.org/10.1145/116873.116880
  19. Lutz, M., 2006, "Programming Python,” O'REILLY.
  20. Ess, A., Leibe, B., Schindler, K. and Van Gool, L., 2009, Moving Obstacle Detection in Highly Dynamic Scene IEEE International Conference on Robotics and Automation (ICRA'09) Kobe, Japan 2009