Robot Path Planning Based on Improved Genetic Algorithm

被引：0

作者：

Zhao, Yuan ^{[1
]}

Gu, Jason ^{[2
]}

机构：

[1] Henan Univ Sci & Technol, Elect & Informat Engn Coll, Luoyang, Peoples R China

[2] Dalhousie Univ, Elect & Comp Engn Dept, Halifax, NS, Canada

来源：

2013 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND BIOMIMETICS (ROBIO) | 2013年

关键词：

mobile robot; path planning; genetic algorithm; grid; MOBILE-ROBOT;

D O I：

暂无

中图分类号：

Q [生物科学];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

This paper proposes an environment model based on grid, and comes up with a two-layer genetic algorithm mechanism as global parallel optimize searching tool to find optimal path. The first layer is responsible for static obstacles avoidance, while the second layer is responsible for dynamic obstacles avoidance, and these two-layer genetic algorithm mechanism has different fitness functions. Simulation results prove the feasibility and effectiveness of the proposed algorithm.

引用

页码：2515 / 2522

页数：8

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