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A Visual-Based Pick and Place on 6 DoF Robot Manipulator Wijaya, Ryan Satria; Pratama, Adhitya; Fatekha, Rifqi Amalya; Soebhakti, Hendawan; Prayoga, Senanjung
Journal of Applied Electrical Engineering Vol. 8 No. 1 (2024): JAEE, June 2024
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaee.v8i1.7358

Abstract

This paper discusses the application of visual servoing on a 6 DOF robotic manipulator for industrial automation. With visual feedback, the manipulator can perform pick and place operations accurately and efficiently. We explore feature- and model-based visual servoing methods and object detection techniques, including deep learning algorithms. The experimental results show that the integration of visual servoing with pick and place method as well as object detection improves the performance of manipulators in industry. This research contributes to the understanding of visual servoing technology in industrial automation. The conclusion shows that the manipulator is more precise in controlling the X-axis shift in the first two experiments, but faces challenges in the third experiment. The success of the system is affected by environmental factors such as lighting. For further development, research is recommended to improve robustness to environmental variations as well as evaluation of execution speed and object positioning accuracy.
Implementasi Perencanaan Jalur menggunakan Algoritma Dijkstra pada Robot Roda Mecanum Prayoga, Senanjung; Ompu Sunggu, Elmaria
Journal of Applied Electrical Engineering Vol. 8 No. 2 (2024): JAEE, December 2024
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaee.v8i2.8470

Abstract

This research develops a robot capable of moving from a starting point to a destination as well as avoiding collisions using Dijkstra's algorithm, which is effective in finding the shortest path. This algorithm is implemented on a mecanum robot equipped with an Arduino microcontroller, mini PC, battery, DC motor with encoder, motor driver, and related software. This study tested five maps with the same starting point and destination, but with different obstacle locations. The test results showed that the mecanum robot managed to find the path and avoid obstacles well. With an average maximum speed of 2.6 m/s, the robot can cover a distance of 3.2 meters without obstacles in 14.96 seconds, and a distance of 4.2 meters with obstacles in 22.82 seconds. This research demonstrates the potential of Dijkstra's algorithm in path planning and robot navigation, and underscores the importance of using the right hardware and software to achieve optimal performance. These results can serve as a basis for further development in the field of robotics, particularly in the application of autonomous robots in dynamic environments.
Implementasi Sistem Kontrol PID untuk Orientasi Robot Hexapod Adriansyah, Yoga; Senanjung Prayoga; Anugerah Wibisana
Journal of Applied Electrical Engineering Vol. 9 No. 1 (2025): JAEE, June 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaee.v9i1.9085

Abstract

This research aims to improve the stability and accuracy of hexapod robot motion in the SAR competition in Indonesia using an adaptive PID control system combined with fuzzy logic. PID control has advantages in linear systems but is less responsive to dynamic conditions, while fuzzy logic can produce a more flexible adaptive response. The proposed system uses IMU sensors to measure directional error, where this data is then processed by fuzzy control to adjust the PID parameters in real time. Tests show that this method results in an average recovery time of 3,06 seconds, a rise time of 1,99 seconds, and an overshoot of approximately 10,00% to 15,60%. These results show an increase in the efficiency of the robot in navigating in complex environments, thus improving the performance in real applications.
Penerapan Visual Servoing Robot Lengan dengan Metode Color Recognition sebagai Pemindah Objek Dua Warna Berbeda Wijaya, Ryan Satria; Rifqi Amalya Fatekha; Senanjung Prayoga; Dzaky Andrawan; Naurah Nazhifah; Mochamad Ari Bagus Nugroho
Journal of Applied Electrical Engineering Vol. 9 No. 1 (2025): JAEE, June 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaee.v9i1.9496

Abstract

Penerapan Visual servoing dengan metode color recognition merupakan sistem yang mengklasifikasikan objek berdasarkan warna dan posisi objek yang terdeteksi melalui kamera untuk menggerakkan servo pada robot lengan. Sistem ini menggunakan Huskylens sebagai kamera yang digunakan untuk mendeteksi warna dan posisi dari sebuah objek dan robot lengan untuk memindahkan objek yang sudah terdeteksi melalui kamera. Dari hasil pengujian, penerapan visual servoing robot lengan dengan metode color recognition dapat berfungsi dengan respon  rata-rata 0,9 detik untuk mengejar objek ketika objek tidak berada di posisi pengambilan dan berfungsi dengan baik untuk mengambil dan meletakkan objek dengan dua warna yaitu biru dan merah ketika berada di posisi pengambilan dengan persentase akurasi deteksi objek 98% serta persentase akurasi pengambilan dan pemindahan objek 100% melalui rentang jarak deteksi minimal 18 – 22 cm diatas objek dan dengan pencahayaan yang terang.
Implementasi Pemetaan Robot Roda Mecanum Otonom Berbasis LIDAR dengan SLAM Prayoga, Senanjung; Diki Sahidan
JURNAL INTEGRASI Vol. 17 No. 1 (2025): Jurnal Integrasi - April 2025
Publisher : Pusat Penelitian dan Pengabdian Masyarakat Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/ji.v17i1.8575

Abstract

This article reviews an autonomous mobile robot with mecanum wheels using localization and mapping with Lidar. The mecanum wheeled robot is capable of autonomously moving from point A to point B. This study aims to determine the level of accuracy and precision in mapping to ensure the robot can operate efficiently, as well as to develop the ability to perform real-time environmental mapping using data obtained from the Lidar A2M12 sensor. It also aims to implement the SLAM (Simultaneous Localization and Mapping) algorithm to simultaneously determine the robot's position and orientation while mapping. For independent movement, the robot must be aware of its surroundings and its position within that environment. The method used is simultaneous localization and mapping using the RPLidar A2M12 sensor and ROS (Robot Operating System). Based on the testing results, the gmapping SLAM error rate is 3.34%, with a sensor distance and angle measurement error of 1.16%. Overall, this autonomous robot can be used even in open areas and with simple obstacles.