Path planning for unmanned aerial vehicles based on genetic programming

Created by W.Langdon from gp-bibliography.bib Revision:1.8178

@InProceedings{Yang:2016:CCDC,

• author = "Xiaoyu Yang and Meng Cai and Jianxun Li",
• booktitle = "2016 Chinese Control and Decision Conference (CCDC)",
• title = "Path planning for unmanned aerial vehicles based on genetic programming",
• year = "2016",
• pages = "717--722",
• abstract = "Path planning system is one of the key component for the unmanned aerial vehicles (UAVs) and mobile robots in modern operational systems used in all sorts of circumstances. Generally, genetic algorithm (GA) plays a big role in dealing with optimisation problems. However, compared to GA, genetic programming (GP) displays better modelling and optimising ability in path planning problem. GP is capable of dealing with UAV and mobile robot path planning problems. GP improves performance by using generalised hierarchical computer programs and optimising evolutionarily. This paper presents an optimised GP method which applies to path planning problem. Several special designed function and symbol operators are proposed and appended to the binary tree structure, as well as the redesigned decoding system. With the combination of selection and reproduction operation, the optimised GP accomplishes the design of path planning. By using the optimised GP method, experiment results display better fitness paths against GA method.",
• keywords = "genetic algorithms, genetic programming",
• DOI = "doi:10.1109/CCDC.2016.7531079",
• month = may,
• notes = "Also known as \cite{7531079}",

}

Genetic Programming entries for Xiaoyu Yang Meng Cai Jianxun Li

Citations