ANALYSIS OPTIMIZATION OF AUTONOMOUS MOBILE ROBOT PATH PLANNING ALGORITHMS

HUSIEN, M. RAVENDRA (2023) ANALYSIS OPTIMIZATION OF AUTONOMOUS MOBILE ROBOT PATH PLANNING ALGORITHMS. S2 thesis, Universitas Mercu Buana - Menteng.

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Abstract

Penelitian mengenai perencanaan jalur untuk mobile robot telah banyak diteliti dan dikembangkan. Pada umumnya, tujuan penelitian mobile robot ini untuk path planning yang diinginkan adalah jalur yang aman, tanpa menabrak rintangan, dan jarak tempuh yang singkat. Dalam penelitian ini, digunakan lima populasi sebagai sampel dan dua nilai iterasi pada percobaan. Dilakukan perbandingan nilai best cost terbaik setiap metode serta lama waktu komputasi yang dihasilkan. Beberapa metode yang diterapkan dalam perencanaan jalur ini antara lain adalah metode particle swarm optimization, ant colony optimization, dan genetic algorithm. Hasil penelitian menunjukkan bahwa metode particle swarm optimization lebih unggul dibandingkan dengan metode ant colony optimization dan genetic algorithm. Hal ini didasarkan pada waktu komputasi yang lebih singkat dan jalur tempuh yang lebih efisien yang dibutuhkan oleh metode particle swarm optimization, dibandingkan dengan metode ant colony optimization dan genetic algorithm. Research on path planning for mobile robots has been widely researched and developed. In general, the goal of mobile robot research for path planning is a safe path without hitting obstacles and a short distance traveled. In this study, five populations were used as samples, and there were two iteration values in the experiment. A comparison of the best cost values for each method and the resulting computing time was carried out. Several methods applied in this route planning include particle swarm optimization methods, ant colony optimization, and genetic algorithms. The research results show that the particle swarm optimization method is superior to the ant colony optimization method and genetic algorithm. This is based on the shorter computing time and more efficient travel paths required by the particle swarm optimization method, compared with the ant colony optimization method and the genetic algorithm.

Item Type:	Thesis (S2)
NIM/NIDN Creators:	55420110028
Uncontrolled Keywords:	Mobile Robot, Path Planning, particle swarm optimization, ant colony optimization, genetic algorithm. mobile robot, path planning, particle swarm optimization, ant colony optimization, genetic algorithm.
Subjects:	600 Technology/Teknologi > 620 Engineering and Applied Operations/Ilmu Teknik dan operasi Terapan > 621 Applied Physics/Fisika terapan
Divisions:	Pascasarjana > Magister Teknik Elektro
Depositing User:	WIDYA AYU PUSPITA NINGRUM
Date Deposited:	16 Aug 2024 03:44
Last Modified:	19 Aug 2024 03:10
URI:	http://repository.mercubuana.ac.id/id/eprint/90301

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