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All Journal J-Innovation
Rendyansyah Rendyansyah
Teknik Elektro Universitas Sriwijaya
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering

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MediaPipe and OpenCV Application for Manipulator Robot Control in Object Retrieval Using Finger-Count Gestures Rendyansyah Rendyansyah
J-Innovation Vol. 15 No. 1 (2026): Jurnal J-Innovation
Publisher : Politeknik Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55600/jipa.v15i1.379

Abstract

The development of robotics and computer vision technologies has opened up opportunities for developing user-friendly Human-Robot Interaction (HRI) systems. This research aims to design and implement a control system for a 4-degree-of-freedom (4-DOF) manipulator robot using finger-count gestures based on MediaPipe and OpenCV. The system utilizes a webcam to capture real-time hand images, which are then processed by MediaPipe Hands to detect 21 hand landmark points to calculate the number of extended fingers. The detected number of fingers is translated into robot control commands, including moving toward the target, picking up objects, moving objects, releasing objects, and returning to the initial position. The manipulator robot is controlled by an Arduino Uno, which regulates the movement of the servo motors via serial communication. The testing results show that the finger-count gesture detection system achieved a success rate of 88% out of 50 trials. Meanwhile, the robot testing for picking up and moving objects obtained a success rate of 80% out of 10 trials. The results of this study demonstrate that the integration of MediaPipe and OpenCV can be effectively used as a real-time manual control medium for manipulator robots based on finger-count gestures.
Implementation of the K-Nearest Neighbor Algorithm on a 4-DoF Manipulator Robot for Color-Based Object Retrieval Rendyansyah Rendyansyah; Irmawan; Hera Hikmarika; Caroline
J-Innovation Vol. 14 No. 2 (2025): Jurnal J Innovation
Publisher : Politeknik Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55600/jipa.v14i2.352

Abstract

This study discusses implementing the K-Nearest Neighbor (K-NN) algorithm on a 4-DoF manipulator robot to pick up objects based on color. The main objective of this study is to design and test a robot control system capable of automatically recognizing, picking up, and moving objects according to color classification. The color detection process is carried out using a camera that extracts color component values in RGB space, which are then classified using the K-NN algorithm with parameter k = 5. The classification results form the basis for the movement of the manipulator robot, which is controlled through cubic trajectory-based trajectory planning, so that the movement of each servo motor joint is smooth and coordinated. Testing was conducted 30 times with three object color categories: red, green, and blue. The experimental results showed that the system could classify colors and pick up objects with a success rate of 96%. Minor failures occurred due to lighting variations that affected color detection results. Overall, the results of this study indicate that the integration of the K-NN algorithm and cubic trajectory is effective in improving the performance of manipulator robots for color-based object recognition and picking tasks and has the potential to be applied in computer vision-based industrial automation systems.
Co-Authors Caroline Hera Hikmarika Irmawan