Journal of Robotics and Control (JRC)
Journal of Robotics and Control (JRC) is an international open-access journal published by Universitas Muhammadiyah Yogyakarta. The journal invites students, researchers, and engineers to contribute to the development of theoretical and practice-oriented theories of Robotics and Control. Its scope includes (but not limited) to the following: Manipulator Robot, Mobile Robot, Flying Robot, Autonomous Robot, Automation Control, Programmable Logic Controller (PLC), SCADA, DCS, Wonderware, Industrial Robot, Robot Controller, Classical Control, Modern Control, Feedback Control, PID Controller, Fuzzy Logic Controller, State Feedback Controller, Neural Network Control, Linear Control, Optimal Control, Nonlinear Control, Robust Control, Adaptive Control, Geometry Control, Visual Control, Tracking Control, Artificial Intelligence, Power Electronic Control System, Grid Control, DC-DC Converter Control, Embedded Intelligence, Network Control System, Automatic Control and etc.
Articles
708 Documents
<![CDATA[Optimized Neural Networks-PID Controller with Wind Rejection Strategy for a Quad-Rotor ]]>
<![CDATA[Chiraz Ben Jabeur]]>;
<![CDATA[Hassene Seddik]]>
<![CDATA[ Journal of Robotics and Control (JRC) Vol 3, No 1 (2022): January ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Yogyakarta ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.18196/jrc.v3i1.11660
<![CDATA[In this paper a full approach of modeling and intelligent control of a four rotor unmanned air vehicle (UAV) known as quad-rotor aircraft is presented. In fact, a PID on-line optimized Neural Networks Approach (PID-NN) is developed to be applied to angular trajectories control of a quad-rotor. Whereas, PID classical controllers are dedicated for the positions, altitude and speed control. The goal of this work is to concept a smart Self-Tuning PID controller, for attitude angles control, based on neural networks able to supervise the quad-rotor for an optimized behavior while tracking a desired trajectory. Many challenges could arise if the quad-rotor is navigating in hostile environments presenting irregular disturbances in the form of wind modeled and applied to the overall system. The quad-rotor has to quickly perform tasks while ensuring stability and accuracy and must behave rapidly with regards to decision making facing disturbances. This technique offers some advantages over conventional control methods such as PID controller. Simulation results are founded on a comparative study between PID and PID-NN controllers based on wind disturbances. These later are applied with several degrees of strength to test the quad-rotor behavior and stability. These simulation results are satisfactory and have demonstrated the effectiveness of the proposed PD-NN approach. In fact, the proposed controller has relatively smaller errors than the PD controller and has a better capability to reject disturbances. In addition, it has proven to be highly robust and efficient face to turbulences in the form of wind disturbances.]]>
<![CDATA[Disinfectant Spraying System with Quadcopter Type Unmanned Aerial Vehicle (UAV) Technology as an Effort to Break the Chain of the COVID-19 Virus ]]>
<![CDATA[Dwi Mutiara Harfina]]>;
<![CDATA[Zaini Zaini]]>;
<![CDATA[Wisnu Joko Wulung]]>
<![CDATA[ Journal of Robotics and Control (JRC) Vol 2, No 6 (2021): November ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Yogyakarta ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.18196/jrc.26129
<![CDATA[Spraying disinfectants as a preventive measure in preventing the transmission of COVID-19 is still being carried out by officers manually by surrounding all parts of the building. Technological developments in the modern era can help and simplify this job. One way to take advantage of technology during the COVID-19 pandemic is to use a drone or an Unmanned Aerial Vehicle (UAV) to spray disinfectants indoors. An unmanned Aerial Vehicle (UAV) is an unmanned aircraft whose flight can be controlled remotely. In this applied research the researchers used a quadcopter UAV which consists of four propellers, each of which is mounted on an 11.1 Volt brushless motor. This motor functions as a propeller drive that uses a current source from LiPo 3S. Based on the research that has been done, the quadcopter is designed using a 2200KV BLDC motor controlled by the SP Racing F3 flight controller. Has been able to fly a quadcopter along with 200ml of disinfectant. However, in order for the quadcopter to be able to lift even greater loads the specifications of the BLDC motor need to be improved]]>
<![CDATA[Magnetic Stirrer with Speed Advisor and Timer Based on Microcontroller ]]>
<![CDATA[I Made Aditya Nugraha]]>;
<![CDATA[I Made Agus Mahardiananta]]>;
<![CDATA[Putu Agus Mahadi Putra]]>;
<![CDATA[I Gede Sura Adnyana]]>
<![CDATA[ Journal of Robotics and Control (JRC) Vol 3, No 1 (2022): January ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Yogyakarta ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.18196/jrc.v3i1.11279
<![CDATA[A magnetic stirrer is a laboratory tool that is used to stir or mix a solution with another solution so that the solution is heterogeneous. Technology and science have now progressed, so in this study, a microcontroller-based magnetic stirrer was designed. This tool is designed with digital speed and time settings, with digital technology, it is hoped that the data reading error of the speed and time of mixing samples can be minimized, efficient in time, relatively easier to use, and produces a homogeneous solution. Based on the results of the analysis that has been carried out by a microcontroller-based magnetic stirrer in a solution with low viscosity from mixing water and syrup, it requires mixing time for 1 minute with low, medium, and high speeds. For a solution with a higher viscosity using water and special grade syrup, it takes 5 minutes at medium and high speeds. To mix water with salt and water with sugar takes 10 minutes at high speed.]]>
<![CDATA[A Sensor Based Assessment Monitoring System for Patients with Neurological Disabilities ]]>
<![CDATA[Bai, Lu]]>
<![CDATA[ Journal of Robotics and Control (JRC) Vol 2, No 6 (2021): November ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Yogyakarta ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.18196/jrc.26127
<![CDATA[The neurological conditions can cause the disability of upper limb and the rehabilitation therapy can help the patients to restore their upper limb motion. However, the current method for upper limb rehabilitation assessment is very basic. The aim of this work is to develop a system and visualize the information to support the doctors and clinicians in the assessment of upper limb motion of patients who are undertaken neurological rehabilitation. Movement tracking including position and orientation have been tracked and data analysis have been done in both time domain and frequency domain. Furthermore, movement smoothness analysis has been done to obtain more information from patients’ movement recovery. The created information visualization can provide objective measurements of patients’ motion recovery and insightful information and for doctors and clinicians including the frequency analysis and movement smoothness analysis. The findings showed the system is able to provide accurate position within 0.1 cm and orientation tracking within 1 degree and meaningful insights for the assessment of upper limb motion functions in daily rehabilitation assessment by providing doctors and clinicians with visualizations of the objective measurements.]]>
<![CDATA[Improving Collision Avoidance Behavior of a Target-Searching Algorithm for Kilobots ]]>
<![CDATA[Alexander Horst]]>;
<![CDATA[Egemen Kaba]]>;
<![CDATA[Rolf Dornberger]]>;
<![CDATA[Thomas Hanne]]>
<![CDATA[ Journal of Robotics and Control (JRC) Vol 2, No 6 (2021): November ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Yogyakarta ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.18196/jrc.26141
<![CDATA[Collision avoidance in the area of swarm robotics is very important. The lacking ability of such collision avoidance is mentioned as one important reason for the sparse distribution of the small test robots named Kilobots. In this research paper, two new algorithms providing a collision avoidance strategy are presented and compared with previous research results. The first algorithm uses randomness to decide which one of several approaching Kilobots are stopped for a defined time before starting to move again. The second algorithm tries to determine the assumed position of approaching Kilobots based on its radio signal strength and then to move away in the opposite direction by rotation. The results, especially of the second algorithm, are promising as the number of collisions can be significantly reduced.]]>
<![CDATA[Synchronizing of Stabilizing Platform Mounted on a Two-Wheeled Robot ]]>
<![CDATA[Mohammad Rabiul Islam]]>;
<![CDATA[Mohammad Rubaiyat Tanvir Hossain]]>;
<![CDATA[Sajal Chandra Banik]]>
<![CDATA[ Journal of Robotics and Control (JRC) Vol 2, No 6 (2021): November ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Yogyakarta ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.18196/jrc.26136
<![CDATA[This paper represents the designing, building, and testing of a self-stabilizing platform mounted on a self-balancing robot. For the self-stabilizing platform, a servo motor is used and for the self-balancing robot, two dc motors are used with an encoder, inertial measurement unit, motor driver, an Arduino UNO microcontroller board. A PID controller is used to control the balancing of the system. The PID controller gains (Kp, Ki, and Kd) were evaluated experimentally. The value of the tilted angle from IMU was fed to the PID controller to control the actuated motors for balancing the system. For the self-stabilizing control part, whenever the robot tilted, it maintained the horizontal position by rotating that much in the opposite direction.]]>
<![CDATA[A New Robotic Application for COVID-19 Specimen Collection Process ]]>
<![CDATA[Cengiz Deniz]]>;
<![CDATA[Gürsel Gökmen]]>
<![CDATA[ Journal of Robotics and Control (JRC) Vol 3, No 1 (2022): January ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Yogyakarta ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.18196/jrc.v3i1.11659
<![CDATA[Covid-19 manual specimen collection process is too critical for health care workers due to they are able to getting infection from Covid-19-patient during the medical interaction. The purpose of this study, a novel robotic application is developed to achieve automatic specimen collection process for new corona virus (COVID-19). This application is a protection tool for health care workers for the Covid-19 pandemic. This robotic application easily and safely complete the sampling process task and assist to health care workers to prevent infection. The application is basically consist of a collaborative robot (COBOT), base plate, fixtures and a gripper. There are co-operation activities between the COBOT and health care worker to complete all tasks. The robotic application has been tested in the plant health care center as a prototype. The cycle-time (192 sec) for the robotic process needs to be improved. The Manual process is still %60 faster than robotic application. The biggest challenge in this application is patient’s mouth and nose physical size changes. Robot movements for the specimen collection in nose and mouth are arranged just based on the fixed point. This needs to be improved according to size changes. Covid-19 specimen collection process with a robotic application has been presented which don’t need any health care worker interaction with patient. This application needs to be improved related with above challenges to make a shelf product. It will create valuable impact and save lives in this pandemic.]]>
<![CDATA[Design and Implementation of Smart Forklift for Automatic Guided Vehicle Using Raspberry Pi 4 ]]>
<![CDATA[Florentinus Budi Setiawan]]>;
<![CDATA[Phoa Marcellino Siva]]>;
<![CDATA[Leonardus Heru Pratomo]]>;
<![CDATA[Slamet Riyadi]]>
<![CDATA[ Journal of Robotics and Control (JRC) Vol 2, No 6 (2021): November ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Yogyakarta ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.18196/jrc.26130
<![CDATA[Automatic Guided Vehicle (AGV) pallet truck is widely used in the industry. This kind of AGV is such a combination of the ordinary AGV used forklift mechanism. The forklift mechanism is employed for lifted up or carrying things from one place to another place. As the technology has been developed along with the industry revolution 4.0, therefore, the activity could be done automatically by using a robot-like AGV pallet truck. Basically, the working principle of the AGV pallet truck is similar to the ordinary forklift whereas the AGV pallet truck is automatically operated. DC motor is applied as the driving force for the uplifting and down lifting process in the forklift mechanism of the AGV pallet truck. DC motor is chosen because it has large torque which is advantageous for lifting loads. Unfortunately, DC motor also owns some disadvantages such as high maintenance fees and less precision. This study proposes a smart forklift mechanism for AGV pallet trucks that utilizes a stepper motor and ultrasonic distance sensor. This smart forklift mechanism is equipped with raspberry pi model B as the main microcontroller and combined with an ultrasonic distance sensor. The result of the ultrasonic distance sensor has an error approaching zero percent so the precision of the height can be fully controlled. Step / Revolution (SPR) method makes the stepper motor can move smoothly like micro-step and also the number of rotations can be controlled as we want.]]>
<![CDATA[Control and Monitoring Automatic Floodgate based on NodeMCU and IOT with Fuzzy Logic Testing ]]>
<![CDATA[Satriya Ramahdika Utama]]>;
<![CDATA[Ahmad Firdausi]]>;
<![CDATA[Galang Persada Hakim]]>
<![CDATA[ Journal of Robotics and Control (JRC) Vol 3, No 1 (2022): January ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Yogyakarta ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.18196/jrc.v3i1.11199
<![CDATA[Flood is still a problem that always been a mayor obstacle in several big cities in Indonesia such as DKI Jakarta. If the rainfall so high and river can be accommodate the rainfall, there will be flooding. So that river water doesn’t overflow, it is necessary to make a floodgate in the river flow. One of the previous studies that has been carried out regarding the control and monitoring of water dam gates is researched by Fahruddin. 2014 from the Faculty of Science and Technology, Makassar State Islamic University: Describes the design of a device capable of monitoring the height of water activity in the reservoir and controlling the floodgates automatically according to the height of water activity. The research that the writer is currently carrying out is the design method which consists of a series of sensors, NodeMCU microcontrollers, and Stepper Motors. The workflow of this system is when the water rises or falls, it send a signal to the sensor. And then the signal will be input for the microcontroller which is then processed to turn on the motor, so that it can open or close the floodgates, and send information to the indicator screen and Telegram application. After the experiment is carried out, it can be said that the system can work properly, namely when the ultrasonic sensor experiment, it was found that the sensor has been sent an output signal that was in accordance with the water level in actual condition. Based on testing using the fuzzy method, it was found that opening value at the floodgate obtained during the test had an average accuracy rate of 91% with an error difference of 9%.]]>
<![CDATA[Real-Time Human Detection Using Deep Learning on Embedded Platforms: A Review ]]>
<![CDATA[Wahyu Rahmaniar]]>;
<![CDATA[Ari Hernawan]]>
<![CDATA[ Journal of Robotics and Control (JRC) Vol 2, No 6 (2021): November ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Yogyakarta ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.18196/jrc.26123
<![CDATA[The detection of an object such as a human is very important for image understanding in the field of computer vision. Human detection in images can provide essential information for a wide variety of applications in intelligent systems. In this paper, human detection is carried out using deep learning that has developed rapidly and achieved extraordinary success in various object detection implementations. Recently, several embedded systems have emerged as powerful computing boards to provide high processing capabilities using the graphics processing unit (GPU). This paper aims to provide a comprehensive survey of the latest achievements in this field brought about by deep learning techniques in the embedded platforms. NVIDIA Jetson was chosen as a low power system designed to accelerate deep learning applications. This review highlights the performance of human detection models such as PedNet, multiped, SSD MobileNet V1, SSD MobileNet V2, and SSD inception V2 on edge computing. This survey aims to provide an overview of these methods and compare their performance in accuracy and computation time for real-time applications. The experimental results show that the SSD MobileNet V2 model provides the highest accuracy with the fastest computation time compared to other models in our video datasets with several scenarios.]]>
