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
24 Documents
Search results for
, issue
"Vol 2, No 6 (2021): November"
:
24 Documents
clear
<![CDATA[Implementation of a Camera Sensor Pixy 2 CMUcam5 to A Two Wheeled Robot to Follow Colored Object ]]>
<![CDATA[Perkasa, Sigit Dani]]>;
<![CDATA[Megantoro, Prisma]]>;
<![CDATA[Winarno, Hendra Ari]]>
<![CDATA[ Journal of Robotics and Control (JRC) Vol 2, No 6 (2021): November (Forthcoming Issue) ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Yogyakarta ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
<![CDATA[This article discusses the design of a colored object follower robot. The colored object used has a simple shape. For the detection process, a wheeled robot that uses sensors based on digital images of Pixy 2. Pixy2 can learn to detect objects that you teach it, just by pressing a button. Additionally, Pixy2 has new algorithms that detect and track lines for use with line-following robots. Pixy2 camera is able to recognize and track all objects whose color has been memorized. In maneuvering, this robot has 2 wheels on the right and left. Movement control is carried out by the Arduino Uno microcontroller board. This robot moves according to the direction of movement of the object. The conclusion obtained in this research is that this wheeled robot can be examined from the left, front and right side objects properly, then it follows the direction of the detected object.]]>
<![CDATA[Small-scale Robot Arm Design with Pick and Place Mission Based on Inverse Kinematics ]]>
<![CDATA[Al Tahtawi, Adnan Rafi]]>;
<![CDATA[Agni, Muhammad]]>;
<![CDATA[Hendrawati, Trisiani Dewi]]>
<![CDATA[ Journal of Robotics and Control (JRC) Vol 2, No 6 (2021): November (Forthcoming Issue) ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Yogyakarta ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
<![CDATA[Robot arm is often used in industry with various tasks, one of which is a pick and place. Rapid prototyping of robot arms is needed to facilitate the development of many industrial tasks, especially on a laboratory scale. This study aims to design a small-scale three degree of freedom (3-DoF) robot arm for pick and place mission using the inverse kinematics method. The mechanical robotic arm system is designed using Solidworks with four servo motors as the actuator. Arduino Mega 2560 is used as a microcontroller in which the inverse kinematic method is embedded. This method is used to move the robot based on the coordinates of the destination pick and place. The test results show that the robot arm can carry out the pick and place mission according to the target coordinates given with the largest average error of about 5 cm. While the error generated between the calculation and computation results is around 3%.]]>
<![CDATA[Real-Time Human Detection Using Deep Learning on Embedded Platforms: A Review ]]>
<![CDATA[Rahmaniar, Wahyu]]>;
<![CDATA[Hernawan, Ari]]>
<![CDATA[ Journal of Robotics and Control (JRC) Vol 2, No 6 (2021): November (Forthcoming Issue) ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Yogyakarta ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
<![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[Smart Robotic Exoskeleton: a 3-DOF for Wrist-forearm Rehabilitation ]]>
<![CDATA[Sabri Shalal, Noor]]>;
<![CDATA[Aboud, Wajdi Sadik]]>
<![CDATA[ Journal of Robotics and Control (JRC) Vol 2, No 6 (2021): November (Forthcoming Issue) ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Yogyakarta ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
<![CDATA[In order to regain the activities of daily living (ADL) for patients suffering from different conditions such as stroke and spinal cord injury, they must be treated with rehabilitation process through programmed exercises. The human motor system can learn through motor learning. This study concerned with the rehabilitation of wrist and forearm joints to restore the ADL through designing and constructing a robotic exoskeleton. The exoskeleton was designed to rehabilitate the patients by providing a 3 degree of freedom (DOF) include flexion/ extension, adduction/abduction, and pronation/ supination movements. It is specified as being portable, comfortable, lightweight, and compatible with the human anatomical structure, in addition to providing a speed and range of motion (ROM) as that of a normal subject. It was designed with SolidWorks software program and constructed with a 3D printer technique using polylactic acid (PLA) plastic material. The overall exoskeleton was controlled with electromyography and angle information extracted using EMG myoware and gyroscope sensors respectively. it was applied for evaluation with 5 normal subjects and 12 subjects of stroke and spinal cord injury (SCI). The results were found that the exoskeleton has a strong effect on regaining muscle activity and increasing the ROMs of wrist and forearm joints. These results give proof of this exoskeleton to be used for performing physiotherapy exercises.]]>
<![CDATA[A Simple Strategy of Control DC-DC Converter as Power Supply on Household Lights ]]>
<![CDATA[Turahyo, Turahyo]]>
<![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.26126
<![CDATA[Light emitting diode (LED) lamps are lighting lamps that have high efficiency with very low power absorption. This lighting lamp is widely used in households, the working voltage is 110-230 volts AC. Under certain conditions, LED light with the driver can also be turned on using a DC voltage at a voltage of 120-125 volts DC. Storage of electrical energy from solar cells generally uses a 12 volt batteries with a large enough current capacity from 5Ah to 400Ah. If the driver LED light is turned on by a battery or battery with a voltage of 12 volts DC from the solar cell, the driver LED light will not light up. This is because the battery / battery voltage level is not high enough to turn on the drive LED light. An electronic device in the form of a DC-DC converter can be utilized to increase the voltage from 12 volts to a higher voltage. In this paper, a DC to DC converter with a voltage multiplier using the Cockcroft-Walton method is designed to be used to turn on LED light for household lighting. After testing, the output voltage from DC to DC is 125.2 volts and the output current is 0.0465 A with a lamp load of 5 watts, while the input voltage is 3.7 volts and the current is 1.49 A.]]>
<![CDATA[Global Saturated Regulator with Variable Gains for Robot Manipulators ]]>
<![CDATA[Brandon Sánchez-García]]>;
<![CDATA[Fernando Reyes-Cortés]]>;
<![CDATA[Basil Al-Hadithi]]>;
<![CDATA[Olga Félix-Beltrán]]>
<![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.26139
<![CDATA[In this paper, we propose a set of saturated controllers with variable gains to solve the regulation problem for robot manipulators in joint space. These control schemes deliver torques inside the prescribed limits of servomotors. The gamma of variable gains is formed by continuous, smooth, and differentiable functions of the joint position error and velocity of the manipulator. A strict Lyapunov function is proposed to demonstrate globally asymptotic stability of the closed-loop equilibrium point. Finally, the functionality and performance of the proposal are illustrated via simulation results and comparative analysis against Proportional-Derivative (PD) control scheme on a two-degrees-freedom direct-drive robot manipulator.]]>
<![CDATA[Dynamic Modeling and Torque Feedforward based Optimal Fuzzy PD control of a High-Speed Parallel Manipulator ]]>
<![CDATA[Zirong Lin]]>;
<![CDATA[Chuangchuang Cui]]>;
<![CDATA[Guanglei Wu]]>
<![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.26133
<![CDATA[Dynamic modeling and control of high-speed parallel manipulators are of importance due to their industrial applications deployed in production lines. However, there are still a number of open problems, such as the development of a precise dynamic model to be used in the model-based control design. This paper presents a four-limb parallel manipulator with Schönflies motion and its simplified dynamic modeling process. Then, in order to fix the issue that computed torque method control (CTC) will spend a lot of time to calculate dynamic parameters in real-time, offline torque feedforward-based PD (TFPD) control law is adopted in the control system. At the same time, fuzzy logic is also used to tune the gains of PD controller to adapt to the variation of external disturbance and compensate the un-modeled uncertainty. Additionally, bottom widths of membership functions of fuzzy controller are optimized by bat algorithm. Finally, three controllers of CTC, TFPD and bat algorithm-based torque feedforwad fuzzy PD controller (BA-TFFPD) are compared in trajectory tracking simulation. Fro the result, compared with TFPD and CTC, BA-TFFPD can lead faster transient response and lower tracking error, which prove the validity of BA-TFFPD.]]>
<![CDATA[Implementation of a Camera Sensor Pixy 2 CMUcam5 to A Two Wheeled Robot to Follow Colored Object ]]>
<![CDATA[Sigit Dani Perkasa]]>;
<![CDATA[Prisma Megantoro]]>;
<![CDATA[Hendra Ari Winarno]]>
<![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.26128
<![CDATA[This article discusses the design of a colored object follower robot. The colored object used has a simple shape. For the detection process, a wheeled robot that uses sensors based on digital images of Pixy 2. Pixy2 can learn to detect objects that you teach it, just by pressing a button. Additionally, Pixy2 has new algorithms that detect and track lines for use with line-following robots. Pixy2 camera is able to recognize and track all objects whose color has been memorized. In maneuvering, this robot has 2 wheels on the right and left. Movement control is carried out by the Arduino Uno microcontroller board. This robot moves according to the direction of movement of the object. The conclusion obtained in this research is that this wheeled robot can be examined from the left, front and right side objects properly, then it follows the direction of the detected object.]]>
<![CDATA[Small-scale Robot Arm Design with Pick and Place Mission Based on Inverse Kinematics ]]>
<![CDATA[Adnan Rafi Al Tahtawi]]>;
<![CDATA[Muhammad Agni]]>;
<![CDATA[Trisiani Dewi Hendrawati]]>
<![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.26124
<![CDATA[Robot arm is often used in industry with various tasks, one of which is a pick and place. Rapid prototyping of robot arms is needed to facilitate the development of many industrial tasks, especially on a laboratory scale. This study aims to design a small-scale three degree of freedom (3-DoF) robot arm for pick and place mission using the inverse kinematics method. The mechanical robotic arm system is designed using Solidworks with four servo motors as the actuator. Arduino Mega 2560 is used as a microcontroller in which the inverse kinematic method is embedded. This method is used to move the robot based on the coordinates of the destination pick and place. The test results show that the robot arm can carry out the pick and place mission according to the target coordinates given with the largest average error of about 5 cm. While the error generated between the calculation and computation results is around 3%.]]>
<![CDATA[Simulation and Arduino Hardware Implementation of DC Motor Control Using Sliding Mode Controller ]]>
<![CDATA[Alfian Ma'arif]]>;
<![CDATA[Abdullah Çakan]]>
<![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.26140
<![CDATA[The research proposed an alternative controller to control the Direct Current (DC) Motor using a sliding mode controller (SMC) in Matlab Simulink simulation and Arduino hardware implementation. The proposed controller, SMC, was designed using the system model (equivalent control) and Lyapunov control design (also to prove the stability). The sliding mode controller had a better response than PID Controller, with no overshoot response in the simulation result. In the Arduino hardware implementation result, the augmented system could reach the reference but has an oscillation and chattering effect in the control signal. The chattering could be reduced by modifying the switching control. Comparing with PID, SMC had a better response with no overshoot. Thus, the SMC could be used as an alternative controller for the DC Motor.]]>
