Multi-agent Path Planning mACO Algorithm in Web3D Mountain Scene

Authors

Fengting Yan, Tongji University, Shanghai 201804, China;
Jinyuan Jia, Tongji University, Shanghai 201804, China;

Abstract

Abstract: There is amount of data in a mountain scene, and the path planning algorithm in it is very complex, so it is not impossible to be shown detailed in Web. Usually the common potential path planning using contours can not find an optimal path because the path is easily cut under the cliff. To solve the above problems, a mACO (mountain ACO) path planning algorithm was addressed for the Web3D application, a planar grid ACO path planning algorithm and a A* path planning were completed in Web3D environment. Then a typical battle scene case was used for the three kinds of algorithms to be compared in effectiveness, efficiency, and FPS. The result can be seen that all the three kinds of algorithms are real-time, but the mACO algorithm is more accurate than the others. Based on the optimal path and using leader-follower idea, a real-time effective multi-agent path planning is implemented.

Recommended Citation

Yan, Fengting and Jia, Jinyuan (2020) "Multi-agent Path Planning mACO Algorithm in Web3D Mountain Scene," Journal of System Simulation: Vol. 28: Iss. 10, Article 4.
Available at: https://dc-china-simulation.researchcommons.org/journal/vol28/iss10/4

First Page

2312

Revised Date

2016-07-14

DOI Link

https://doi.org/

Last Page

2320

CLC

TP391

Recommended Citation

Yan Fengting, Jia Jinyuan. Multi-agent Path Planning mACO Algorithm in Web3D Mountain Scene[J]. Journal of System Simulation, 2016, 28(10): 2312-2320.