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.
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<![CDATA[Mobile Security Vehicle’s based on Internet of Things ]]>
<![CDATA[Muchammad Husni]]>;
<![CDATA[R. V. H. Ginardi]]>;
<![CDATA[K. Gozali]]>;
<![CDATA[R. Rahman]]>;
<![CDATA[A. S. Indrawanti]]>;
<![CDATA[M. I. Senoaji]]>
<![CDATA[ Journal of Robotics and Control (JRC) Vol 2, No 6 (2021): November ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Yogyakarta ]]>
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DOI: 10.18196/jrc.26135
<![CDATA[The purpose of this research is to design and build a mobile security vehicle based on the Internet of Things (IoT) that combines to Arduino-based microcontroller, internet networks, and the needed hardware. The design is intended to monitor and control the vehicle condition and monitor the vehicle location based on IoT. This research uses hardware and software components. The hardware uses the Arduino-based microcontroller that connects to some modules. This research uses Relay Module 2 Channel HL-525 to control the vehicle machine, GPS Module Neo-7M to get the vehicle location, SIM800L Module to connect to the internet network, and ACS-712 Voltage sensor to detect the voltage in the vehicle electricity. This research uses multi-platform (web application) as the component software to monitor and control the vehicle condition and its location. The result of this research is Mobile Security Vehicle’s System Based on Arduino where the system can satisfy some functional needs such as can monitoring motorcycle location, controlling alarm, and motorcycle electricity to avoid theft through a web application that can be used in multi-platform.]]>
<![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 ]]>
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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[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 ]]>
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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 ]]>
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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 ]]>
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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[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 ]]>
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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[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 ]]>
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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.]]>
<![CDATA[Second Order Integral Fuzzy Logic Control Based Rocket Tracking Control ]]>
<![CDATA[Iswanto Iswanto]]>;
<![CDATA[Irfan Ahmad]]>
<![CDATA[ Journal of Robotics and Control (JRC) Vol 2, No 6 (2021): November ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Yogyakarta ]]>
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DOI: 10.18196/jrc.26142
<![CDATA[Fuzzy logic is a logic that has a degree of membership in the vulnerable 0 to 1. Fuzzy logic is used to translate a quantity that is expressed using language. Fuzzy logic is used as a control system because this control process is relatively easy and flexible to design without involving complex mathematical models of the system to be controlled. The purpose of this paper is to present a fuzzy control system implemented in a rocket tracking control system. The fuzzy control system is used to keep the rocket on track and traveling at a certain speed. The signal from the fuzzy logic control system is used to control the rocket thrust. The fuzzy Logic System was chosen as the controller because it is able to work well on non-linear systems and offers convenience in program design. Fuzzy logic systems have a weakness when working on systems that require very fast control such as rockets. With this problem, fuzzy logic is modified by adding second-order integral control to the modified fuzzy logic. The proposed algorithm shows that the missile can slide according to the ramp path at 12 m altitude of 12.78 at 12 seconds with a steady-state error of 0.78 under FLC control, at 10 m altitude of 10.68 at 10 seconds with a steady-state error of 0.68 with control integral FCL, at a height of 4 m is 4.689 at 4 seconds with a steady-state error of 0.689 with a second-order integral control of FCL. The missile can also slide according to the parabolic path with the second-order integral control of FCL at an altitude of 15.47 in the 4th minute with a steady-state error of 0.]]>
<![CDATA[Development of a Prototype Autonomous Electric Vehicle ]]>
<![CDATA[Mohammed, Aisha Abdul]]>;
<![CDATA[Abdullahi, Aliyu]]>;
<![CDATA[Ibrahim, Amina]]>
<![CDATA[ Journal of Robotics and Control (JRC) Vol 2, No 6 (2021): November ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Yogyakarta ]]>
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DOI: 10.18196/jrc.26137
<![CDATA[The paper presents an Autonomous Electric Vehicle with obstacle avoidance system. This research work made use of ultrasonic sensors, the principle of distance measurements and calculations as well as detecting obstacle on its path. The device consists of three ultrasonic sensors that detect object for each left, right and front of the vehicle, based on developed and installed codes in the Arduino microcontroller and displays the range using ISIS Proteus 8 electronic modelling software. The minimum and maximum range of object detections is 2cm to 400cm respectively. However, the measured distance was from 25cm to 150cm and the corresponding calculated distances using oscilloscope waveforms are 28.10cm and 148.3cm. The difference between the measured and calculated distance was 5.4% on average. GPS navigates the vehicle autonomously to its destination using an algorithm for navigation based on reactive behavior. The vehicle is powered by rechargeable batteries (4 lithium ion batteries) which are charged using external power source by connecting into electricity grid. Furthermore, a solar panel has been utilized as a secondary source of power to charge the batteries. This reduces the dependency of the vehicle on external power sources. The vehicle is capable of moving for about 20m to and fro and avoiding obstacle on its path.]]>
<![CDATA[Design and Programming of 5 Axis Manipulator Robot with GrblGru Open Source Software on Preparing Vocational Students’ Robotic Skills ]]>
<![CDATA[Marsono Marsono]]>;
<![CDATA[Yoto Yoto]]>;
<![CDATA[Agus Suyetno]]>;
<![CDATA[Riana Nurmalasari]]>
<![CDATA[ Journal of Robotics and Control (JRC) Vol 2, No 6 (2021): November ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Yogyakarta ]]>
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DOI: 10.18196/jrc.26134
<![CDATA[The rapid development of technology at the end of this decade, the industrial world is changing the human resources they have using the help of robot technology. The use of a robot was chosen because of the accuracy and precision that it can do in doing the job. In addition, robotic technology requires only one programming to do many things. Thus, there are many advantages for companies by using robotic technology in their production processes. This research aims to designing and building arm robot prototype to teach the robotics programming language. The result of this research is an arm robot prototype with Arduino Mega 2560 based programming. In addition, the robot movement programming uses the open source GrblGru software Grbl based. The GrblGru used for interpreting G-code and to convert pulse and direction information to control the stepper motor. This research concludes that there are 5 importance steps on develop the arm robot prototype, 1. Analyze; 2. Design; 3. Develop; 4. Evaluate; and 5. Implementation. With the GrblGru software the movements of arm robot prototype can work on simulation mode and control mode, there for students easier to study robotics programming language.]]>
