An efficient Genetic Algorithm for the Global Robot Path Planning Problem

被引：0

作者：

Alnasser, Sarah ^{[1
]}

Bennaceur, Hachemi ^{[1
]}

机构：

[1] Al Imam Mohammad Ibn Saud Islamic Univ IMSIU, Dept Comp Sci, POB 5701, Riyadh 11432, Saudi Arabia

来源：

2016 SIXTH INTERNATIONAL CONFERENCE ON DIGITAL INFORMATION AND COMMUNICATION TECHNOLOGY AND ITS APPLICATIONS (DICTAP) | 2016年

关键词：

Genetic algorithm; global path planning problem; mobile robot; static environment; fitness function; grid-based environment;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Path planning problem (PPP) is a challenging problem in several real-life applications and needs to be developed and implemented in a suitable manner. For that purpose we designed an efficient Genetic Algorithm (GA) for modeling and solving PPP. The proposed GA exploits an adequate solution representation and a smart crossover operator, and introduces a significant fitness function involving several criteria of robot motion. We conducted a comprehensive experiments of the proposed algorithm and we compared it against two different approaches of the literature: Genetic Algorithm and Tabu search algorithms. Simulation results show the efficiency and effectiveness of our genetic algorithm in comparison with the other planners in term of solution quality and execution time.

引用

页码：97 / 102

页数：6

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