Global navigation in dynamic environments using case-based reasoning

Autonomous Robots

Volumn 14, Issue 1, 2003, Pages 71-91

  Kruusmaa, Maarja ^a  

^a HALMSTAD UNIVERSITY   (Sweden)

Author keywords

Case based reasoning; Dynamic environments; Obstacle avoidance; Robot navigation

Indexed keywords

ALGORITHMS; COLLISION AVOIDANCE; COMPUTER SIMULATION; KNOWLEDGE BASED SYSTEMS; MOBILE ROBOTS; ROBOT LEARNING; UNCERTAIN SYSTEMS;

CASE-BASED REASONING; DYNAMIC ENVIRONMENTS; ROBOT NAVIGATION;

MOTION PLANNING;

EID: 0037269763     PISSN: 09295593     EISSN: None     Source Type: Journal    
DOI: 10.1023/A:1020979520454     Document Type: Article

References (28)

1. Aamodt, A. and Plaza, E. 1994. Case-based reasoning: Foundational issues, methodological variations and system approaches. AI Communications, 7:39-59.
2. Arkin, R.C. 1995. Reactive robotic systems. In Handbook of Brain Theory and Neural Networks, M. Arbib (Ed.), MIT Press: Cambridge, MA, pp. 793-796.
3. Azarm, K. and Schmidt, G. 1994. Integrated mobile robot motion planning and execution in changing indoor environments. In Proc. of the IEEE Inter. Conf. of Intelligent Robots and Systems (IROS'94), Vol. 1, pp. 298-305.
4. Bourbakis, N.G. 1995. Knowledge extraction and acquisition during real-time navigation in unknown environments. Inter. Journal of Pattern Recognition and Artificial Intelligence, 9(1):83-99.
5. Branting, L.K. and Aha, D.W. 1995. Stratified case-based reasoning: Reusing hierarchical problem solving episodes. In Proc. of the Fourteenth International Joint Conference on Artificial Intelligence, Montreal, Canada.
6. Crowder, R.M., McKendrick, R., Rowe, R., Auriol, E., and Tellefsen, M. 2000. Maintanance of robotic systems using hypermedia and case-based reasoning. In Proc. of the 2000 IEEE International Conference on Robotics and Automation, San-Francisco, CA, April 2000.
7. Elfes, A. 1987. Sonar-based real-world maping and navigation. IEEE Journal of Robotics and Automation, 3(3):249-265.
8. Fagg, A.H., Lotspeich, D.L., and Bekey, G.A. 1994. A reinforcement-learning approach to reactive control policy design for autonomous robots. In Proc. of the 1994 IEEE Conf. on Robotics and Automation.
9. Fox, S. and Leake, D.B. 1995. Combining case-based planning and introspective reasoning. In Proc. of the Sixth Midwest Artificial Intelligence and Cognitive Science Society Conference, Carbondale, IL, April 1995.
10. Goel, A.K., Ali, K.S., Donnellan, M.W., Gomex de Silva Garza, A., and Callatine, T.J. 1994. Multistrategy adaptive path planning. IEEE Expert, 9(6):57-65.
11. Haigh, K.Z. and Veloso, M. 1995. Route planning by analogy. In Case-Based Reasoning Research and Development, Proceedings of ICCBR-95, Springer-Verlag: Berlin, pp. 169-180.
12. Haigh, K.Z. and Veloso, M.M. 1998. Planning, execution and learning in a robotic agent. In AIPS-98, pp. 120-127.
13. Hu, H. and Brady, M. 1997. Dynamic global path planning with uncertainty for mobile robots in manufacturing. IEEE Transactions on Robotic and Automation, 13(5):760-767.
14. Jarvis, R. and Kang, K. 1986. A new approach to robot collision-free path planning. In Robots in Australia's Future Conference, pp. 71-79.
15. Kruse, E. and Wahl, F.M. 1998. Camera-based observation of obstacle motions to derive statistical data for mobile robot motion planning. Proc. Of IEEE Conference of Robotics and Automation, Vol. 1, pp. 662-667.
16. Kruusmaa, M. 2001. Repeated path planning for mobile robots in uncertain environments. In Proc. of the IASTED Int. Conf. of Robotics and Applications, Nov. 19-22, Clearwater, FL, pp. 226-231.
17. Kruusmaa, M. 2002. Repeated path planning for mobile robots in dynamic environments. Ph.D. Thesis, Chalmers University of Technology, Gothenburg, Sweden, 2002.
18. Likhachev, M. and Arkin, R.C. 2001. Spatio-temporal case-based reasoning for behavioral selection. In Proc. of the 2001 IEEE International Conference on Robotics and Automation (ICRA), Seoul, Korea, pp. 1627-1634.
19. Moorman, K. and Ram, A. 1992. A Case-based approach to reactive control for autonomous robots. In AAAI Fall symposium on "AI for Real-World Autonomous Mobile Robots," Cambridge, MA.
20. Murphy, R.R., Hughes, K., Marzilli, A., and Noll, E. 1999. Integrating explicit path planing with reactive control of mobile robots using trulla. Robotics and Autonomous Systems, 27:225-246.
21. Ram, A., Arkin, R., Boone, G., and Pearce, M. 1994. Using genetic algorithms to learn reactive control parameters for autonomous robotic navigation. Adaptive behaviour, 2(3):277-305.
22. Thrun, S. 1997. To know or not to know: On the utility of models in mobile robotics. AI Magazine, 18(1):47-52.
23. Thrun, S. 1998. Learning metric-topological maps for indoor mobile robot navigation. Artificial Intelligence, 99(1):21-71.
24. Vasudevan, C. and Ganesan, K. 1994. Case-based path planning for autonomous underwater vehicles. In Proc. of 1994 IEEE International Symposium on Intelligent Control, August 16-18, pp. 160-165.
25. Wallner, F., Kaiser, M., Fredrich, H., and Dillmann, R. 1994. Integration of topological and geometrical planning in a learning mobile robot. In IEEE-RSJ Conference on Intelligent Robots and Systems (IROS'94), Munich, Germany.
26. Watson, I. and Marir, F. 1994. Case-based reasoning: A review. The Knowledge Engineering Review, 9(4).
27. Zelek, J.S. 1999. Dynamic issues for mobile robot real-time discovery and path planning. In Proc. of Computational Intelligence in Robotics and Automation (CIRA'99), pp. 232-237.
28. Zelinsky, A. 1994. Using path transforms to guide the search for findpath in 2D. The Int. Journal of Robotics Research, 13(4):315-325.