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Arduino-based Automatic Fish Feeding Device Prototype Nugraha, Muhammad Iqbal; Cahyono, Bagus Dwi
Journal of Computer Science Advancements Vol. 1 No. 5 (2023)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jsca.v1i5.641

Abstract

Consuming fish food is an important part of the process of growing and maintaining fish. In general, fish food is given by conventionally throwing it by hand. However, this is not done at the same time every day. Based on the problems above, the researchers made a prototype of an Arduino-based automatic fish feeding device. The aim of this research is to determine the effectiveness of the automatic fish feeder prototype. In the prototype that the researchers made using several main components such as Arduino Uno as the system or brain of this prototype, servo motor, 20 x 4 LCD, buttons, Real Time Clock (RTC), and several jumper cables. The effectiveness of this tool can be seen from the test results, where the automatic fish feeder prototype succeeded in providing fish food according to a predetermined schedule.
AUTONOMOUS MOBILE ROBOT DENGAN MENGGUNAKAN METODE SIMULTANEOUS LOCALIZATION AND MAPPING BERBASIS LIDAR Maulana, Mashur Arbi; Novian, Reynaldi; Nugraha, Muhammad Iqbal; Setiawan, I Made Andik
Prosiding Seminar Nasional Inovasi Teknologi Terapan Vol. 2 No. 01 (2022): Prosiding Seminar Nasional Inovasi Teknologi Terapan
Publisher : Politeknik Manufaktur Negeri Bangka Belitung

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Abstract

Autonomous mobile robot is a robot that can move independently from point to point. Which is important for working in dangerous area. To move independently, the robot must be able to identify its environment and know its position in the form of two-dimensional map. This research used Simultaneous Localization And Mapping (SLAM) method combined with of RPLidar A1M8 sensor and Robot Operating System(ROS) for identification the evironment. As a results, Autonomous robot is capable of mapping and delivering information of the robot can map and localize its position in an environment with mapping error 0,21% and 1,14% localization. Distance measurement in various angle tendts to stable with mean error 0,98%. Overall, the robot can be used in an empty area or an area with simple obstacle.