Implementasi Metode Simultaneous Localization and Mapping pada Autonomous Mobile Robot Menggunakan Sensor LiDAR

Syahbana, Elfano Sultan (2024) Implementasi Metode Simultaneous Localization and Mapping pada Autonomous Mobile Robot Menggunakan Sensor LiDAR. Diploma thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Autonomous Mobile Robot (AMR) telah menjadi bagian penting dari pertumbuhan industri 4.0 untuk meningkatkan produktivitas dan otomasi sistem logistik. Kemampuan AMR untuk mengenali lingkungannya dan melokalisasikan posisinya secara akurat diperlukan untuk menjadikan AMR line follower autonomous. Studi ini berkonsentrasi pada penciptaan metode pemetaan dan lokalisasi untuk AMR yang menggunakan metode Simultaneous Localization and Mapping (SLAM). SLAM memungkinkan AMR untuk menentukan posisinya di dalam peta dua dimensi (2D) dan membuat peta lingkungannya secara real-time. Dalam pelaksanaannya, sensor deteksi dan pengukuran jarak (LiDAR) digunakan untuk mengumpulkan data lingkungan. Selain itu, Robot Operating System (ROS) berfungsi sebagai platform untuk mengintegrasikan berbagai bagian hardware dan software AMR. Environment yang diberikan ROS memudahkan proses pengembangan dan perubahan sistem AMR. Setelah melakukan pengujian, hasil pembacaan jarak pada sensor RPLidar A1M8 memiliki rata – rata error sebesar 0,77% terhadap jarak sebenarnya, hasil pengujian mapping dengan Hector SLAM menggunkan sensor RPLidar A1M8 terhadap arena pengujian memiliki rata–rata error sebesar 0,1978%, dan dari hasil Ujicoba lokalisasi yang dilakukan dengan Hector SLAM (fungsi transform) terhadap arena percobaan memiliki rata–rata error hingga 1,523%.
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Autonomous Mobile Robots (AMR) have become an important part of the growing industry 4.0 to improve productivity and automation of logistics systems. The ability of AMR to recognise its environment and localise its position accurately is required to make AMR line follower autonomous. This study concentrates on creating a mapping and localisation method for AMR that uses the Simultaneous Localisation and Mapping (SLAM) method. SLAM allows the AMR to determine its position in a two-dimensional (2D) map and create a real-time map of its environment. In the implementation, light distance detection and measurement (LiDAR) sensors are used to collect highly accurate environmental data. In addition, the Robot Operating System (ROS) serves as a platform for integrating the various hardware and software parts of the AMR. The robust development environment provided by ROS eases the process of developing and changing the AMR system. After testing, the results of distance readings on the RPLidar A1M8 sensor have an average error of 0.77% against the actual distance, the results of Mapping tests with Hector SLAM using the RPLidar A1M8 sensor against the test arena have an average error of 0.1978%, and from the results of localisation tests conducted with Hector SLAM (transform function) against the
experimental arena have an average error of up to 1.523%.

Item Type:	Thesis (Diploma)
Uncontrolled Keywords:	Autonomous Mobile Robot (AMR), Simultaneous Localization and Mapping (SLAM), RobotOperating System (ROS), Light Detection and Ranging (LiDAR).
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK1007 Electric power systems control T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK6592.A9 Automatic tracking. T Technology > TS Manufactures T Technology > TS Manufactures > TS253 Die-Casting
Divisions:	Faculty of Vocational > 36304-Automation Electronic Engineering
Depositing User:	Elfano Sultan Syahbana
Date Deposited:	27 Sep 2024 02:08
Last Modified:	27 Sep 2024 02:08
URI:	http://repository.its.ac.id/id/eprint/115705

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