@inproceedings{ac712722c0cc4f5a9b10b76cb5827fa6,
title = "Path planning and replanning for intelligent robot based on improved ant colony algorithm",
abstract = "The effectiveness of path planning and path replanning for intelligent robot using improved ant colony algorithm is explored in this paper. For the purpose of avoiding falling into local optimum and preventing iterative stagnant, this paper describes a new algorithm named stochastic self-adaptive ant colony algorithm to improve the basic ant colony algorithm. Based on the improved ant colony algorithm, the approaches of path planning and path replanning are presented in this paper. Aiming at improving the speed of the algorithm and simplifying the objective function of traditional path planning, this paper presents a principle of eliminating the path nodes.Finally, some constrast emulators are designed.The simulation results proves that the improved ant colony algorithm has strong adaptability in intelligent robot's path path planning and replanning.",
keywords = "Ant colony algorithm, Intelligent robot, Path planning, Path replanning",
author = "Tang, {Bi Wei} and Zhu, {Zhan Xia} and Qun Fang and Ma, {Wei Hua}",
year = "2013",
doi = "10.4028/www.scientific.net/AMM.390.495",
language = "英语",
isbn = "9783037858332",
series = "Applied Mechanics and Materials",
pages = "495--499",
booktitle = "Mechanical and Aerospace Engineering IV",
note = "2013 4th International Conference on Mechanical and Aerospace Engineering, ICMAE 2013 ; Conference date: 20-07-2013 Through 21-07-2013",
}