On-line real-time path planning of mobile robots in dynamic uncertain environment

Journal of Zhejiang University: Science

Volumn 7, Issue 4, 2006, Pages 516-524

  Zhuang, Hui Zhong ^a   Du, Shu Xin ^a   Wu, Tie Jun ^a  

^a STATE KEY LABORATORY OF INDUSTRIAL CONTROL TECHNOLOGY   (China)

Author keywords

Autoregressive (AR) prediction; Desirable direction angle; Dynamic obstacle; Mobile robot; On line real time path planning

Indexed keywords

COLLISION AVOIDANCE; COMPUTER SIMULATION; MOTION PLANNING; OPTIMIZATION;

ALGORITHM REACHABILITY; AUTOREGRESSIVE (AR) MODEL; AUTOREGRESSIVE (AR) PREDICTION; DESIRABLE DIRECTION ANGLE; DYNAMIC OBSTACLE; DYNAMIC UNCERTAIN ENVIRONMENT; ENVIRONMENT INFORMATION; ONLINE REAL TIME PATH PLANNING; OPTIMIZATION CAPABILITY; OPTIMIZATION INDEX;

MOBILE ROBOTS;

EID: 33744748355     PISSN: 10093095     EISSN: None     Source Type: Journal    
DOI: 10.1631/jzus.2006.A0516     Document Type: Article

References (12)

1. Fujumura, K., 1992. Route Planning for Mobile Robots amidst Moving Obstacles. IROS'92, p.1751-1758.
2. Fiorinio, P., Shiller, Z., 1998. Motion planning in dynamic environments using velocity obstacles. Int. Journal of Robotics Research, 17(7): 760-772.
3. Kalman, R., 1960. A new approach to linear filtering and prediction problem. Journal of Basic Engineering, 82(Series D): 35-45.
4. Lee, D.T.L., Morf, M., Friedlander, B., 1981. Recursive least squares ladder estimation algorithms. IEEE Trans. Acoustics, Speech, Signal Processing, 29(3): 627-641. [doi:10.1109/TASSP.1981.1163587]
5. Luo, R., Chen, T., 1999. Target Tracking by Grey Prediction Theory and Look-ahead Fuzzy Logic Control. Proceedings of the IEEE International Conference on Robotics and Automation, p.1176-1181.
6. Makhoul, J., 1975. Linear Prediction: A Tutorial Review. Proc. IEEE, 63: 561-580.
7. Rude, M., 1997. Collision avoidance by using space-time representations of motion processes. Autonomous Robots, 4(1): 101-119. [doi:10.1023/A:1008863220740]
8. Sen, A., Srivastava, M., 1990. Regression Analysis: Theory, Methods and Applications. Springger-Verlay, New York.
9. Shensa, M.J., 1981. Recursive least squares lattice algorithms-A geometrical approach. IEEE Trans. Auto. Control, 26(3): 695-702. [doi:10.1109/TAC.1981.1102682]
10. Takeshi, A., 1994. Motion Planning for Multiple Obstacles Avoidance of Autonomous Mobile Robot Using Hierarchical Fuzzy Rule. Proceedings of IEEE International Conference on Multi-sensor Fusion and Integration for Intelligent System (MFI'94), Las Vegas, p.265-271.
11. Tang, P., Zhang, Q., Yang, Y.M., 2000. Studying on Path Planning and Dynamic Obstacle Avoiding of Soccer Robot. Proceedings of the 3rd World Congress on Intelligent Control and Automation, University of Science and Technology of China, Hefei, p.1244-1247.
12. Zhu, Q., 1991. Hidden Markov model for dynamic obstacle avoidance of mobile robot navigation. IEEE Trans. on Robotics and Automation, 7(3): 390-396. [doi:10.1109/70.88149]