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Efektivitas ROS Development Studio sebagai Simulator Pendukung Pengembangan Algoritma Platform Robotika Kevin Julianto Effendy; Nova Eka Budiyanta
Jurnal Elektro Vol 13 No 2 (2020): Jurnal Elektro: Oktober 2020
Publisher : Program Studi Teknik Elektro, Fakultas Biosains, Teknologi, dan Inovasi, Universitas Katolik Indonesia Atma Jaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25170/jurnalelektro.v13i2.1972

Abstract

This study aims to analyze robotics simulation tools that can be used to support algorithm development in the robot modelling process. There are several simulation tools for robot algorithm modelling that are popularly used by robotics developers. This study focuses on analyzing the effectiveness based on the features of the Robot Operating System Development Studio (ROSDS) and MATLAB as a development simulation platform using the comparative method. The results of this study claim that ROSDS is more effective than MATLAB in terms supporting the development of robotics simulation because ROS is used as a middleware in ROSDS that connects the communication between the program with the robot, so that makes it easier for making robotics simulation and ROSDS is easier to access than MATLAB. The trial case study of developing trajectory algorithm in the robot arm was carried out in this research to support the statement above, and it worked out well.
Design and Implementation of a Vision-based Wheeled Mobile Robot Using HSV Color Segmentation and P-D Control Wira Aditama; David Herianto; Nico Fernando; Carolus Henry; Nova Eka Budiyanta
Jurnal Elektro Vol 18 No 1 (2025): Jurnal Elektro: April 2025
Publisher : Program Studi Teknik Elektro, Fakultas Biosains, Teknologi, dan Inovasi, Universitas Katolik Indonesia Atma Jaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25170/jurnalelektro.v18i1.6892

Abstract

This study presents the design and implementation of a wheeled mobile robot capable of detecting and tracking a ping-pong ball using vision-based processing. The system integrates a Raspberry Pi 3 Model B+ as the main controller, a Raspberry Pi Camera Rev 1.3 for visual input, and DC motors driven by an L298N motor driver for actuation. Object detection is achieved through color segmentation in the HSV color space using the OpenCV library, followed by morphological filtering and contour analysis. A proportional-derivative (PD) control algorithm is employed to adjust motor speeds dynamically based on the ball's horizontal position in the frame. The experimental results demonstrate that the robot can successfully detect and follow a ping-pong ball, although it exhibits limitations in processing speed and motion stability. The average frame rate during operation was 5 FPS, which is sufficient for basic tracking tasks but suboptimal for high-speed applications. This project highlights the feasibility of vision based robotic systems for simple object tracking tasks.