Rendyansyah Rendyansyah’s research while affiliated with Sriwijaya University and other places

This research presents the development of a U-Arm model robot with three degrees of freedom, utilizing Inverse Kinematic calculations. The novelty of this project lies in its precise control of the robot arm's movements through advanced kinematic algorithms. Inverse Kinematics is a mathematical process used to determine the joint angles of the robot arm from known (x, y, z) coordinates of the end-effector and the lengths of each link. The robotic arm consists of four links with lengths of 8.2 cm, 15 cm, 16 cm, and 18.4 cm, respectively, and is equipped with a gripping module for object manipulation. The methodology involves calculating the joint angles required for the desired end-effector position, ensuring accurate and efficient movement. Testing results indicate an average coordinate error of 7.13%, demonstrating the system's precision and reliability. This error rate provides valuable insights into the performance and potential areas for improvement in the kinematic model. Additionally, this research includes the development of a program to control the servo motor speed using For and delay functions. This program enhances the robot's operational efficiency by allowing precise speed adjustments, which are crucial for various applications. Overall, this study contributes to the field of robotics by offering a detailed analysis of kinematic control and program development for a multi-link robotic arm, highlighting its potential for practical applications.

Humanoid robots are designed to mimic human structures and utilize cameras to process visual input to identify surrounding objects. However, previous studies have focused solely on object detection, overlooking both the complexities of real-world implementation and the significance of calculating the distance between objects and the robot. This study proposes a system that employs the you only look once (YOLO) algorithm to detect various objects in the proximity of a robot. Using a dataset of primary data collected in a laboratory, the detected objects are from 12 classes, including humans, chairs, tables, cabinets, computers, books, doors, bottles, eggs, learning modules, cups, and hands, with each class comprising 1500 data points. Two YOLO architectures, namely tiny YOLOv3 and tiny YOLOv4, are assessed for their performance in object detection, with the tiny YOLOv4 demonstrating a superior accuracy of 82.99% compared to tiny YOLOv3. Evaluation under simulated conditions yields an accuracy of 74.16%, while in real-time scenarios, accuracies are 61.66% under bright conditions and 38.33% under dim conditions, affirming tiny YOLOv4’s efficacy. Moreover, this study reveals an average error distance of 31% between an object and the robot in real-time conditions. The developed system enhances human–robot interaction capabilities via data transmission.

Multi-robot arm control is the result of the development of advanced robotics technology. With the advancement in the field of human-machine interface, controlling robot arms has become more efficient and can be done intuitively by humans. In this study, we designed three robot arms of 4-DoF, each of which is controlled by a computer in a visual program interface. This research aims to develop a human-machine interface-based multi-robot arm control system that allows humans to interact with the robots directly. The movement method of each robot uses Trajectory Planning, which works when the operator gives motion commands through the interface display. Multi-robot communication with a computer using USB hub serial format. The computer is the master, and each Arduino on the robot is the enslaved. Three robot arms have been tested and controlled by the HMI computer, and all of them move according to the commands of the operator. The time required by each robot to complete its mission is ± 10 seconds. The results of this study are expected to open new opportunities in the application of robotics in various fields, such as the manufacturing industry, health services, and transportation.

Hydroponics is a technique that allows easy cultivation of fresh and hygienic vegetables, even with limited space. Recent innovations in hydroponic development have resulted in a smart showcase prototype, which is controlled using Sugeno fuzzy techniques. This prototype uses a DC fan to maintain a stable temperature and humidity level. This invention is both ecologically friendly and portable, making it suitable for a wide range of users, including apartment residents. Experimental results using the fuzzy method show that this prototype can effectively support indoor hydroponic techniques, with fan rotation ranging from 180 to 255 rpm based on variations in room temperature and humidity. The showcase successfully maintained a stable temperature range of 28–30 °C and a humidity of 60–70% RH. In addition, out of 12 vegetable samples tested for 14 days, 7 kale stems showed significant growth. Overall, this smart showcase prototype offers the potential to bring hydroponics indoors and promote fresh vegetable cultivation.

Jam digital merupakan alat untuk memudahkan manusia dalam melihat waktu. Jam digital terdiri dari processor, display disusun sesuai format jam, dan Real Time Clock. Di sekolah menengah atas, siswa harus dikenalkan dan dididik tentang pembelajaran elektronik dan pemrograman sebagai tingkat dasar untuk memulai membuat sistem digital. Oleh karena itu, kegiatan pengabdian kepada masyarakat melalui pelatihan pemrograman arduino sebagai jam digital kepada Siswa SMA Negeri 1 Indralaya Ogan Ilir sebanyak 20 orang. Kegiatan pelatihan ini bertujuan untuk memberikan pemahaman dan keterampilan siswa melalui pemrogaman arduino sebagai jam digital. Metode kegiatan yang digunakan adalah sosialisasi, presentase, praktikum, demonstrasi dan evaluasi. Berdasarkan hasil pelatihan bahwa siswa dapat memahami materi yang diberikan dengan baik mencapai 95% siswa. Siswa mampu membuat program jam digital dan menyesaikan projek sederhana dengan hasil yang baik.

Tanjung Pinang II Village is one of the districts in Tanjung Batu, Ogan Ilir Regency, South Sumatra, which is currently developing its potential to become a tourist village through an agro-park. However, the process of transforming the village into a tourism and educational area for the community has not yet implemented technology. Therefore, in this community service, a smart greenhouse was developed and implemented in Tanjung Pinang II Village. The methods used in this community service included situational analysis, greenhouse construction, counseling and training, as well as evaluation, analysis, and conclusion. The constructed greenhouse is equipped with temperature and humidity sensors to measure the conditions inside the room. The greenhouse is built with a steel frame and uses UV plastic for its roof and walls. The results of the community service showed that the village residents and the community benefited from the greenhouse in the process of developing Tanjung Pinang II Village as an ecotourism area.

Humans are very dependent on technology to lighten their work in various fields. One robotics technology that is often applied is in industrial and medical areas. Robotics is a machine that can work automatically or receive instructions from the operator. In general, the application of robots in the industry provides advantages in terms of time and production results. One example of robots in Industry is Robotic Arms, such as medical robots, assembling, welding, picking up and moving objects, and others. In this study, the robot arm has freedom within 4-DoF, and the robot is controlled based on hand gestures using the Template Matching method. The robotic arm navigates based on hand gestures captured by the camera and then processed in the computer. The object used is adjusted to the experimental instrument. The experimental results show that the arm robot 4-DoF can move based on commands from hand gestures with a success rate of 90%.

Robots are widely used in industry. Robots generally have a control system or intelligence embedded in the processor. The robots consist of mobile mode, manipulator, and their combination. Mobile robots usually use wheels, and manipulator robots have limited degrees of freedom. Both have their respective advantages. Mobile robots are widely applied to environments with flat floor surfaces. The manipulator robots are applied to a static environment to produce, print, and cut material. In this study, the robot arm 4 Degree of Freedom (DoF) is integrated with a computer. The computer controls the whole system, where the operator can control the Robot based on voice commands. The operator's voice is one person only with different intonations. Voice command recognition uses the Mel-Frequency Cepstral Coefficients (MFCC) and Artificial Neural Networks (ANN) methods. The MFCC and ANN programs are processed in the computer, and the program output is sent to the Robot via serial communication. There are nine types of voice commands with different MFCC patterns. ANN training data for each command is 10 data, so the total becomes 90. In this experiment, the Robot can move according to voice commands given by the operator. Tests for each voice command are ten experiments, so the total experiment is 90 times with a success rate of 94%. There is only one operator, and experiments have not yet been carried out with the voices of several operators. The error occurred because there were several similar patterns during system testing.

The mobile robot is a system that can move according to function and task. An example is an industrial robot taking objects using a remote control system. Robots controlled using a manual remote system are generally carried out on mobile robots. Many researchers have developed manual control methods, such as image or sound-based robot control. In this study, the mobile robot was applied in an unobstructed room and controlled using voice commands. The methods used are Mel-Frequency Cepstral Coefficients (MFCC) and Support Vector Machine (SVM). MFCC is a characteristic identification of voice command patterns such as “forward”, “backward”, “left”, “right”, and “stop.” SVM is used to recognize voice command patterns based on the value of the MFCC for each pattern. The experiment has been carried out 50 times with a success rate of 96%. Overall the robot can be controlled by voice commands with good movement.

Teknologi robot telah digunakan dalam bidang otomasi industri, medis, pertanian, dan lain-lain. Umumnya robot terdiri dari dua tipe yaitu mobile dan non-mobile. Robot tipe mobile dapat berpindah dari satu posisi menuju ke posisi lain, sedangkan robot tipe non-mobile bersifat statis pada basis. Salah satu contoh dari robot tipe non-mobileialah berbentuk manipulator atau lengan. Pada penelitian ini dirancang lengan robot dengan sistem perekem gerak dalam mengambil objek. Lengan robot ini memiliki empat derajat kebebasan (4 Degree of Freedom). Prototype robot ini telah dilengkapi dengan gripper untuk mengambil objek. Adapun sistem kendali pada robot menggunakan sistem perekam koordinat yang ter-program di dalam Komputer menggunakan Cubic Trajectory. Percobaan robot lengan dilakukan di Laboratorium, dan objek menyesuaikan keadaan robot. Robot tersebut dikendalikan oleh program komputer berdasarkan pergerakan yang diinginkan, setelah itu komputer memberikan perintah kepada motor servo pada setiap joint. Adapun hasil percobaan menunjukkan bahwa robot lengan dapat dikendalikan secara manual oleh operator menggunakan komputer,Robot juga mampu ber-navigasi (pergerakan) otomatis berdasarkan rekam gerak yang ditentukan oleh operator.