Proceedings of the 6th International Conference on Applied Engineering, ICAE 2023, 7 November 2023, Batam, Riau islands, Indonesia

Research Article

Design of Barelang F.1 Robot Using Genetic Algorithm Method for Multiplication OnUneven Floor

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  • @INPROCEEDINGS{10.4108/eai.7-11-2023.2342947,
        author={Diono  Diono and Yoel Panangian Tambunan and Fadli  Firdaus and Adlian  Jefiza},
        title={Design of Barelang F.1 Robot Using Genetic Algorithm Method for Multiplication OnUneven Floor},
        proceedings={Proceedings of the 6th International Conference on Applied Engineering, ICAE 2023, 7 November 2023, Batam, Riau islands, Indonesia},
        publisher={EAI},
        proceedings_a={ICAE},
        year={2024},
        month={1},
        keywords={genetic algorithm stabilization robotic movement},
        doi={10.4108/eai.7-11-2023.2342947}
    }
    
  • Diono Diono
    Yoel Panangian Tambunan
    Fadli Firdaus
    Adlian Jefiza
    Year: 2024
    Design of Barelang F.1 Robot Using Genetic Algorithm Method for Multiplication OnUneven Floor
    ICAE
    EAI
    DOI: 10.4108/eai.7-11-2023.2342947
Diono Diono1,*, Yoel Panangian Tambunan1, Fadli Firdaus1, Adlian Jefiza1
  • 1: Politeknik Negeri Batam
*Contact email: diono@polibatam.ac.id

Abstract

A quadruped robot is a legged robot that has four legs to move. Barelang F.1 is a robot that moves with inverse kinematics, with inverse kinematics this robot can move by giving a value to each joint on robot’s legs [1]. Barelang F.1 is a robot that we built to compete in the Indonesian Robot Contest (KRI) event. In that competition, we find that there are still several challenges that our robot can't handle. Uneven obstacles and inclined planes will be a challenge for the Barelang F.1 robot now because we still don’t have a method to overcome that challanges. The purpose of making this journal is to conduct research on these existing problems and find solutions for that. So we choose the genetic algorithm method to see if this method will be the best solution to our robot to overcome the problems that we encounter. After a several test we find that the result from genetic algorithm method it had a small error that can make the robot to stabilize itself but for that small error it took a long time to process, so this method can be applied to find the best angle for the robot to stabilize itself but it can used during the competition due to the time that it takes to proceed the calculation.