Full Text:   <2871>

CLC number: TP242.6

On-line Access: 

Received: 2004-08-28

Revision Accepted: 2004-12-02

Crosschecked: 0000-00-00

Cited: 2

Clicked: 6281

Citations:  Bibtex RefMan EndNote GB/T7714

-   Go to

Article info.
Open peer comments

Journal of Zhejiang University SCIENCE A 2005 Vol.6 No.7 P.697-706

http://doi.org/10.1631/jzus.2005.A0697


Cooperative co-evolution based distributed path planning of multiple mobile robots


Author(s):  WANG Mei, WU Tie-jun

Affiliation(s):  Institute of Intelligent Systems & Decision Making, Zhejiang University, Hangzhou 310027, China

Corresponding email(s):   mwang@iipc.zju.edu.cn, tjwu@iipc.zju.edu.cn

Key Words:  Cooperative co-evolution, Multiple mobile robot, Cooperative collision avoidance, Path planning


WANG Mei, WU Tie-jun. Cooperative co-evolution based distributed path planning of multiple mobile robots[J]. Journal of Zhejiang University Science A, 2005, 6(7): 697-706.

@article{title="Cooperative co-evolution based distributed path planning of multiple mobile robots",
author="WANG Mei, WU Tie-jun",
journal="Journal of Zhejiang University Science A",
volume="6",
number="7",
pages="697-706",
year="2005",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.2005.A0697"
}

%0 Journal Article
%T Cooperative co-evolution based distributed path planning of multiple mobile robots
%A WANG Mei
%A WU Tie-jun
%J Journal of Zhejiang University SCIENCE A
%V 6
%N 7
%P 697-706
%@ 1673-565X
%D 2005
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.2005.A0697

TY - JOUR
T1 - Cooperative co-evolution based distributed path planning of multiple mobile robots
A1 - WANG Mei
A1 - WU Tie-jun
J0 - Journal of Zhejiang University Science A
VL - 6
IS - 7
SP - 697
EP - 706
%@ 1673-565X
Y1 - 2005
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.2005.A0697


Abstract: 
This paper proposes novel multiple-mobile-robot collision avoidance path planning based on cooperative co-evolution, which can be executed fully distributed and in parallel. A real valued co-evolutionary algorithm is developed to coordinate the movement of multiple robots in 2D world, avoiding C-space or grid net searching. The collision avoidance is achieved by cooperatively co-evolving segments of paths and the time interval to pass them. Methods for constraint handling, which are developed for evolutionary algorithm, make the path planning easier. The effectiveness of the algorithm is demonstrated on a number of 2D path planning problems.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

Reference

[1] Alami, R., 1996. A Fleet of Autonomous and Cooperative Mobile Robots. Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems, 3:1112-1117.

[2] Berlanga, A., Isasi, P., Sanchis, A., Molina, J.M., 2000. Coevolutive Adaptation of Fitness Landscape for Solving the Testing Problem. IEEE International Conference on Systems, Man and Cybernetics, p.3846-3851.

[3] Bennewitz, M., Burgard, W., Thrun, S., 2001. Optimizing Schedules for Prioritized Path Planning of Multi-robot Systems. Proceedings of IEEE International Conference on Robotics and Automation, 1:271-276.

[4] Cao, Y.U., Fukunaga, A.S., Kahng, A.B., Meng, F., 1995. Cooperative Mobile Robotics: Antecedents and Directions. Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems, 1:226-234.

[5] Fischer, C., Buss, M., Schmidt, G., 1996. Hierarchical Supervisory Control of Service Robot Using Human-Robot Interface. Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems, p.1408-1416.

[6] Fujii, T., Arai, Y., Asama, H., Endo, I., 1998. Multilayered Reinforcement Learning for Complicated Collision Avoidance Problems. Proceedings of IEEE International Conference on Robotics and Automation, p.2185-2191.

[7] Fujimori, A., Tani, S., 2002. A Navigation of Mobile Robots with Collision Avoidance for Moving Obstacles. IEEE International Conference on Industrial Technology, 1:1-6.

[8] Goldberg, D.E., 1989. Genetic Algorithm in Search optimization and Machine Learning. Wesley Publishing Company.

[9] Koren, Y., Borenstein, J., 1991. Potential Field Methods and Their Inherent Limitations for Mobile Robot Navigation. Proceedings of IEEE International Conference on Robotics and Automation, 2:1398-1404.

[10] Koziel, S., Michalewicz, Z., 1999. Evolutionary algorithms, homomorphous mappings and constrained parameter optimization. Evolutionary Computation, 7(1):19-44.

[11] Latombe, J.C., 1991. Robot Motion Planning. Kluwer Academic, Boston.

[12] Michalewicz, Z., Attia, N., 1994. Evolutionary Optimization of Constrained Problems. Proceedings of 3rd Conference on Evolutionary Programming, p.98-108.

[13] Michalewicz, Z., Schoenauer, M., 1996. Evolutionary algorithms for constrained parameter optimization problems. Evolutionary Computation, 4(1):1-32.

[14] Myung, H., Kim, J.H., Fogel, D., 1995. Preliminary Investigation on Constrained Problems. Proceedings of 4th Conference on Evolutionary Programming, p.449-463.

[15] Potter, M.A., 1997. The Design and Analysis of a Computational Model of Cooperative Coevolution. Ph.D Thesis, George Mason University.

[16] Salichs, M.A., Moreno, L., 2000. Navigation of mobile robots: open questions. Robotica, 18:227-234.

[17] Schoenauer, M., Michalewicz, Z., 1996. Evolutionary Computation at the Edge of Feasibility. Proceedings of 4th Conference on Parallel Problems Solving from Nature, 1141:245-254.

[18] Schoenauer, M., Xanthakis, S., 1993. Constrained GA Optimization. Proc. of 5th Int. Conf. on Genetic Algorithms, p.573-580.

[19] Shibata, T., Fukuda, T., 1993. Intelligent Motion Planning by Genetic Algorithm with Fuzzy Critic. Proceeding of 8th IEEE Symp. on Intelligent Control, p.565-570.

[20] Sim, K.B., Chun, H.B., Lee, D.W., 2001. Dynamic Behavior Control of Autonomous Mobile Robots Using Schema Co-evolutionary Algorithm. Proceedings of IEEE International Symposium on Industrial Electronics, 1:560-565.

[21] Smierzchalski, R., Michalewicz, Z., 2000. Modeling of ship trajectory in collision situations by an evolutionary algorithm. IEEE Transactions on Evolutionary Computation, 4(3):227-241.

[22] Xiao, J., Michalewicz, Z., Zhang, L., Trojanowski, K., 1997. Adaptive evolutionary planner/navigator for mobile robots. IEEE Transactions on Evolutionary Computation, 1(1):18-28.

[23] Zheng, C.W., Ding, M.Y., Zhou, C.P., 2002. Cooperative Path Planning for Multiple Air Vehicles Using a Co-evolutionary Algorithm. Proceedings of International Conference on Machine Learning and Cybernetics, Beijing, 1:219-224.

Open peer comments: Debate/Discuss/Question/Opinion

<1>

Please provide your name, email address and a comment





Journal of Zhejiang University-SCIENCE, 38 Zheda Road, Hangzhou 310027, China
Tel: +86-571-87952783; E-mail: cjzhang@zju.edu.cn
Copyright © 2000 - 2024 Journal of Zhejiang University-SCIENCE