Real-time color-based sorting robotic arm system

Jia, Yonghui; Yang, Guojun; Saniie, Jafar

doi:10.1109/eit.2017.8053385

Cited by 14 publications

(5 citation statements)

References 9 publications

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“…The Bluetooth is connected from the mobile phone to the HC05 Bluetooth module [2], [16]- [21] as a receiver from the Arduino application. The PCA9685 module is [22] used to control a servo motor with six servo motors.…”

Section: Methodsmentioning

confidence: 99%

Accelerometer Implementation as Feedback on 5 Degree of Freedom Arm Robot

Kunal

Arfianto

Poetro

et al. 2020

jrc

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The research investigated the automatic control system implemented with the 5 DOF (Degree of Freedom) arm robot control system using the closed-loop control method with the MPU 6050 sensor, which integrated the rotation of the MG995 motor servo as a feedback function. The control of this robot used android-based application, in which the app sends data of the rotate angle for each servo motor rotated to a certain angle. The HC -05 Bluetooth received the data and the Arduino UNO R3 microcontroller processed them. The microcontroller managed every rotation of each servo motor that integrated with an MPU6050 sensor with serial monitor communication to display the rotation of each servo motor. The test results obtained by the standard deviation value showed how large the sample diversity was. The result of this study showed a standard deviation correlation with the number of sample diversity. The higher the standard deviation value, the more sample data spread (data diverse or varies). Otherwise, the smaller the standard deviation value, the more homogenous the sample data. If the standard deviation equals zero, it indicates that the sample has identical data. The highest standard deviation value from servo motor 1 is 5.20, servo motor 2 and 3 are 1.00, servo motor 4 is 2.89, and servo motor 5 is 2.9.

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Section: Methodsmentioning

confidence: 99%

Accelerometer Implementation as Feedback on 5 Degree of Freedom Arm Robot

Kunal

Arfianto

Poetro

et al. 2020

jrc

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show abstract

“…They used MATLAB for programming the codes for image processing and the robotic arm. Jia et al [10] used image processing to detect the color of the objects and then used the Phantom X Reactor robotic arm to pick and place the object. The arm was controlled using the ArbotiX-M microcontroller.…”

Section: Literature Reviewmentioning

confidence: 99%

Automated Object Sorting System with Real-Time Image Processing and Robotic Gripper Mechanism Control

Sanwar,

Ahmed

2023

J. Eng. Adv.

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This work represents an industrial sorting system where image processing is accompanied using a pick-and-place robotic gripper. The sorting of objects is done based on their shape and color. Here the color and shape of different objects are identified using image processing. For this, a webcam is used to capture images of the object in real-time and then process them via a digital computer. Python programming language is used for image processing in this work. After successfully identifying the color and shape of an object, the object is picked and placed at the desired position using the robotic gripper. Controlling the gripper mechanism is also executed using the Python programming language. It is controlled using the Arduino Uno microcontroller and a few DC servo motors. The gripper can move from 0° to 180°. The objects are brought in front of the camera using a belt conveyor system. After the complete fabrication and assembly, 4 objects of different shapes and colors are used to sort objects at 4 different angles. The objects are picked from 90° and is sorted in either 0°, 45°, 135°, or 180° position. This research work not only gives information about robotics but also can help industries sort complex objects automatically without any human interaction.

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“…The first camera is for PBVS and the second camera for IBVS. Jia [16] used the Phantom X Reactor manipulator, one camera, and the Pseudoinverse Jacobian method for inverse kinematics. In his article, Jia does not explain the inverse kinematics mechanism used, but rather focuses on detection systems and electronic hardware.…”

Section: Imentioning

confidence: 99%

Robot Manipulator Control with Inverse Kinematics PD-Pseudoinverse Jacobian and Forward Kinematics Denavit Hartenberg

Agustian

Daratha

Faurina

et al. 2021

J. Elektron. dan Telekomun.

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This paper presents the development of vision-based robotic arm manipulator control by applying Proportional Derivative-Pseudoinverse Jacobian (PD-PIJ) kinematics and Denavit Hartenberg forward kinematics. The task of sorting objects based on color is carried out to observe error propagation in the implementation of manipulator on real system. The objects image captured by the digital camera were processed based on HSV-color model and the centroid coordinate of each object detected were calculated. These coordinates are end effector position target to pick each object and were placed to the right position based on its color. Based on the end effector position target, PD-PIJ inverse kinematics method was used to determine the right angle of each joint of manipulator links. The angles found by PD-PIJ is the input of DH forward kinematics. The process was repeated until the square end effector reached the target. The experiment of model and implementation to actual manipulator were analyzed using Probability Density Function (PDF) and Weibull Probability Distribution. The result shows that the manipulator navigation system had a good performance. The real implementation of color sorting task on manipulator shows the probability of success rate cm is 94.46% for euclidian distance error less than 1.2 cm.

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Real-time color-based sorting robotic arm system

Cited by 14 publications

References 9 publications

Accelerometer Implementation as Feedback on 5 Degree of Freedom Arm Robot

Accelerometer Implementation as Feedback on 5 Degree of Freedom Arm Robot

Automated Object Sorting System with Real-Time Image Processing and Robotic Gripper Mechanism Control

Robot Manipulator Control with Inverse Kinematics PD-Pseudoinverse Jacobian and Forward Kinematics Denavit Hartenberg

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