Claim Missing Document
Check
Articles

Found 9 Documents
Search

The ROS: Kinetic Kame for Humanoid Robot BarelangFC Susanto Susanto; Junito Suroto; Riska Analia
JURNAL INTEGRASI Vol 13 No 1 (2021): Jurnal Integrasi - April 2021
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/ji.v13i1.2686

Abstract

A collaborative robot such as humanoid robot which able to play soccer consist tons of software framework such as servo controller, vision system, strategy receiver and transmitter, sensors, and coordination system. All these frameworks needed to be integrated to simplify the command of creating the complexity of the robot behaviors. To overcome these problems, the Robot Operating System (ROS) can be implemented on each robot. This paper presented the implementation of the ROS: Kinetic Kame in order to integrated the whole framework which is existed in the robot. To verify the performance of this system, some experiments has been done in real-time application. From the experimental results, the ROS: Kinetic Kame able to integrate each software framework of the robot in very good response.
Industry 4.0: Hand Recognition on Assembly Supervision Process Riska Analia; Andika Putra Pratama; Susanto Susanto
JURNAL INTEGRASI Vol 13 No 1 (2021): Jurnal Integrasi - April 2021
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/ji.v13i1.2757

Abstract

In the assembly industry, the process of assembling components is very important in order to produce a quality product. Assembly of components should be carried out sequentially based on the standards set by the company. For companies that still operate the assembly process manually by employee, sometimes errors occur in the assembly process, which can affect the quality of production. In order to be carried out the assembly process according to the procedure, a system is needed that can detect employee hands when carrying out the assembly process automatically. This study proposes an artificial intelligence-based real-time employee hand detection system. This system will be the basis for the development of an automatic industrial product assembly process to welcome the Industry 4.0. To verify system performance, several experiments were carried out, such as; detecting the right and left hands of employees and detecting hands when using accessories or not. From the experimental results it can be concluded that the system is able to detect the right and left hands of employees well with the resulting FPS average of 15.4.
Establishing ROS on Humanoid Soccer Robot-BarelangFC Software System Susanto Susanto; Eko Priono; Riska Analia
JURNAL INTEGRASI Vol 13 No 2 (2021): Jurnal Integrasi - Oktober 2021
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/ji.v13i2.3333

Abstract

Humanoid robot is built on several sub-programs or systems which is integrated to each main programs in order to command the robot to move as a soccer player. Each main programs namely as a movement system, a visual sense system (vision), a sub-controller system, and a game strategy. Currently, each of main system constructed using different programming language, for instance: the vision system used python while the others used C and LUA for the movement kinematics. Employing different programming language will affect to response system because each of main system need to be integrated using socket in the beginning process. Robot response will be slow and cost a lot of memory usage. Therefore, in this paper will present a migrating process into robot operating system (ROS) and switch all the robot main system into python language. The integrated program will be examined in real-time application while the robot moved on the field. We used a python ROS in order to make the robot play autonomously on the field.
Real-time Coordinate Estimation for Self-Localization of the Humanoid Robot Soccer BarelangFC Susanto Susanto; Taufiq Tegar Pratama; Riska Analia
JURNAL INTEGRASI Vol 14 No 2 (2022): Jurnal Integrasi - Oktober 2022
Publisher : Pusat Penelitian dan Pengabdian Masyarakat Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/ji.v14i2.4110

Abstract

In implementation, of the humanoid robot soccer consists of more than three robots when played soccer on the field. All the robots needed to be played the soccer as human done such as seeking, chasing, dribbling and kicking the ball. To do all of these commands, it is required a real-time localization system so that each robot will understand not only the robot position itself but also the other robots and even the object on the field’s environment. However, in real-time implementation and due to the limited ability of the robot computation, it is necessary to determine a method which has fast computation and able to save much memory. Therefore, in this paper we presented a real-time localization implementation method using the odometry and Monte Carlo Localization (MCL) method. In order to verify the performance of this method, some experiment has been carried out in real-time application. From the experimental result, the proposed method able to estimate the coordinate of each robot position in X and Y position on the field.
Improving STEM Capability of Islamic Boarding School Students in Batam Through Robotics Training Hendawan Soebhakti; Eko Rudiawan Jamzuri; Senanjung Prayoga; Rifqi Amalya Fatekha; Anugerah Wibisana; Susanto Susanto; Riska Analia; Fitriyanti Nakul; Adlian Jefiza; Eka Mutia Lubis; Budiana Budiana; Ika Karlina Laila Nur Suciningtyas; Ahmad Riyad Firdaus
Engagement: Jurnal Pengabdian Kepada Masyarakat Vol 7 No 2 (2023): November 2023
Publisher : Asosiasi Dosen Pengembang Masyarajat (ADPEMAS) Forum Komunikasi Dosen Peneliti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29062/engagement.v7i1.1350

Abstract

Conducting robotics training as a community service to improve basic knowledge of Science, Technology, Engineering, and Mathematics (STEM) for students is one of the ways to improve their basic knowledge of Science, Technology, Engineering, and Mathematics (STEM) for students is one of the most important aspects of the facing the industrial era 4.0 and society 5.0. Through the Service-Learning approach, this community service by collaborating with Granada International in Batam by involving 29 students, consisting of 7 students from class X, 15 students from class XI, and the rest from class XII, class XI students, and the rest from class XII. The results of mentoring through robotics training were able to increase the average STEM skills of students by 38.15%. In addition, the activity was successfully implemented with participant satisfaction levels above 50% for the subject matter, instructor, and training equipment. Only 17% of the trainees stated that the training time was insufficient, especially for practicum.
Penempatan Pendeteksi Masker Untuk Pencegahan Penyebaran Covid di Kampus dan Pelabuhan Pamungkas, Daniel Sutopo; Sani, Abdulah; Gautama, Adytia; Analia, Riska; Hasnira; F Prebianto, Nanta; Rahmawati, Zahira; Siregar, Bismar; Al-Tsurayya, Maw’Izhah; Saragi, Elsa; Yudiarta, Geri
Journal of Applied Community Engagement Vol 2 No 1 (2022): Journal of Applied Community Engagement (JACE)
Publisher : ISAS (Indonesian Society of Applied Science)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (393.925 KB) | DOI: 10.52158/jace.v2i1.308

Abstract

At this time the world has been hit by the Covid-19 pandemic since 2019. The government advises the Indonesian people to follow the Health protocol. One of them is to wear a mask when we travel to public places. Some public places that are difficult to avoid include schools/campuses and ports. The people of the Riau Archipelago are very dependent on sea transportation modes. The movement of people is very massive in both places. Therefore, people are expected to always be disciplined in using masks in crowded places. To ensure and remind the public to always wear a mask is rather difficult. So we developed a mask detection device and stored it in public places. This tool leverages artificial intelligence technology with deep learning. This tool works very well, it can remind people who don't wear masks, even those who wear masks that aren't right.
Tiny-YOLO distance measurement and object detection coordination system for the BarelangFC robot Susanto, Susanto; Ricardo Silitonga, Jony Arif; Analia, Riska; Jamzuri, Eko Rudiawan; Pamungkas, Daniel Sutopo
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 6: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i6.pp6926-6939

Abstract

A humanoid robot called BarelangFC was designed to take part in the Kontes Robot Indonesia (KRI) competition, in the robot coordination division. In this division, each robot is expected to recognize its opponents and to pass the ball towards a team member to establish coordination between the robots. In order to achieve this team coordination, a fast and accurate system is needed to detect and estimate the other robot’s position in real time. Moreover, each robot has to estimate its team members’ locations based on its camera reading, so that the ball can be passed without error. This research proposes a Tiny-YOLO deep learning method to detect the location of a team member robot and presents a real-time coordination system using a ZED camera. To establish the coordinate system, the distance between the robots was estimated using a trigonometric equation to ensure that the robot was able to pass the ball towards another robot. To verify our method, real-time experiments was carried out using an NVDIA Jetson NX Xavier, and the results showed that the robot could estimate the distance correctly before passing the ball toward another robot.
Object Detection and Pose Estimation with RGB-D Camera for Supporting Robotic Bin-Picking JAMZURI, EKO RUDIAWAN; ANALIA, RISKA; SUSANTO, SUSANTO
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 11, No 1: Published January 2023
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v11i1.128

Abstract

ABSTRAKTujuan dari penelitian ini adalah untuk mendeteksi objek dan mengestimasi pose objek menggunakan kamera RGB-D. Dalam penelitian ini, kami mengusulkan pemrosesan data pada citra RGB dan citra depth saja, tanpa menggunakan point cloud, seperti pada umumnya. Metode yang diusulkan mendeteksi posisi dan orientasi objek menggunakan DRBox-v2 dari Region of Interest (ROI), yang sebelumnya diperoleh dari pendeteksian pada penanda ArUco. Hasil deteksi objek kemudian diskalakan dan digunakan pada citra depth untuk mendapatkan perkiraan posisi dan orientasi objek. Dari sisi pendeteksi objek, usulan metode memperoleh nilai Average Precision (AP) sebesar 0,740. Sedangkan untuk estimator pose, usulan metode menghasilkan kesalahan posisi rata-rata 13,36 mm dan kesalahan orientasi rata-rata 0,75 derajat. Metode yang diusulkan berpotensi menjadi alternatif sistem deteksi objek dan estimasi pose pada kamera RGB-D yang tidak memerlukan pemrosesan point cloud dan tidak memerlukan model referensi objek.Kata kunci: deteksi objek, estimasi pose, DRBox, ArUco, bin-picking ABSTRACTThis study aims to detect objects and estimate the object's pose using an RGB-D camera. In this study, we proposed data processing on RGB images and depth images only, without using point clouds, as in general. The proposed method detected the object's position and orientation using the DRBox-v2 from the Region of Interest (ROI), which was previously obtained from detecting ArUco markers. The object detection results were then scaled and used in the depth image to get the object's approximate position and orientation. In object detection, the proposed method obtained an Average Precision (AP) value of 0.740. As for the pose estimator, our method generated an average position error of 13.36 mm and an average orientation error of 0.75 degrees. Therefore, this method can be an alternative object detection and pose estimation system on an RGB-D camera that does not require point cloud processing and an object reference model.Keywords: object detection, pose estimation, DRBox, ArUco, bin-picking
Robotics training to improve STEM skills of Islamic boarding school students in Batam Eko Rudiawan Jamzuri; Hendawan Soebhakti; Senanjung Prayoga; Rifqi Amalya Fatekha; Anugerah Wibisana; Fitriyanti Nakul; H. Hasnira; Riska Analia; S. Susanto; Ryan Satria Wijaya; Ika Karlina Laila Nur Suciningtyas; Widya Rika Puspita; Eka Mutia Lubis; Adlian Jefiza; B. Budiana; Ahmad Riyad Firdaus
Journal of Community Service and Empowerment Vol. 5 No. 1 (2024): April
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/jcse.v5i1.26895

Abstract

One potential approach to addressing the challenges posed by the advent of Industry 4.0 and Society 5.0 is to offer robotics training. This endeavor aims to enhance students' foundational understanding of STEM (Science, Technology, Engineering, and Mathematics) disciplines. The study involved collaborating with the Pondok Pesantren Granada, an Islamic Boarding School located in Batam, to provide robotics training as community service activities. The study included 29 trainees: 15 from class XI and 7 from classes X and XII. The teaching was conducted using a combination of didactic instruction, interactive discourse, and hands-on exercises. Trainees are administered a written examination to assess their proficiency level before and after the training program. The training outcomes exhibited a significant improvement in the mean STEM proficiency of trainees, with an increase of 38.15%. Furthermore, a series of activities have been effectively implemented, resulting in trainee satisfaction ratings exceeding 50% concerning course materials, trainer, and teaching equipment. A mere 17% of the individuals undergoing training expressed dissatisfaction with the allocated time, particularly the hands-on component's duration.