scholarly journals Automatic Control of Color Sorting and Pick/Place of a 6- DOF Robot Arm

2021 ◽  
Vol 54 (3) ◽  
pp. 435-443
Author(s):  
Lim Wei Jie ◽  
Teoh Poh Sen ◽  
Nor Maniha Abdul Ghani ◽  
Mohammad Fadhil Abas
Keyword(s):  
Robot Arm ◽  
Servo Motor ◽  
Color Sensor ◽  
Wireless Control ◽  
Pick And Place ◽  
Color Sensors ◽  
Industrial Use ◽  
Input Variables ◽  
Arm Motion ◽  
Six Degree Of Freedom

This work focuses on the implementation and design of a six degree of freedom, 6-DOF control of automatic color sorting and pick and place tasks for a robot arm using wireless controlling interface – Blynk apps. Based on the collaboration between the servo motor and input color sensor, this wireless control of automatic color sorting robot arm provides a powerful wireless control GUI (Graphics User Interface) and to enable the method for manual color sorting mode. The color sorting mode is performed once the mode is turned on by the user. The robot arm able to differentiate the colors of the object (input) and categorize or classify the object to the correct places automatically. It provides a stable, efficient, and precision results without any vibration of control as the main target for this project. In this work, six servo motors were used to realize the real robotic arm for industrial use. Five servos were operated to control the entire robot arm motion including the base, shoulder, and elbow as well as one servo is reserved for the positioning of the end effector. Two input variables namely TSC3200 Color Sensors & HC-SR04 Ultrasonic Sensors were employed as the input for the robot arm. The output variable mainly focused on the servo motor as the links for the robot arm to reposition and change the motion for the entire system.

scholarly journals Multimodal Mixed Reality Impact on a Hand Guiding Task with a Holographic Cobot

2020 ◽  
Vol 4 (4) ◽  
pp. 78
Author(s):  
Andoni Rivera Pinto ◽  
Johan Kildal ◽  
Elena Lazkano
Keyword(s):  
Augmented Reality ◽  
Industrial Production ◽  
User Study ◽  
Haptic Feedback ◽  
Mixed Reality ◽  
Robot Arm ◽  
Pick And Place ◽  
Place Task ◽  
Guidance Technique ◽  
The Impact

In the context of industrial production, a worker that wants to program a robot using the hand-guidance technique needs that the robot is available to be programmed and not in operation. This means that production with that robot is stopped during that time. A way around this constraint is to perform the same manual guidance steps on a holographic representation of the digital twin of the robot, using augmented reality technologies. However, this presents the limitation of a lack of tangibility of the visual holograms that the user tries to grab. We present an interface in which some of the tangibility is provided through ultrasound-based mid-air haptics actuation. We report a user study that evaluates the impact that the presence of such haptic feedback may have on a pick-and-place task of the wrist of a holographic robot arm which we found to be beneficial.

ROBOTIC HANDWRITING

2005 ◽  
Vol 02 (01) ◽  
pp. 105-124 ◽  
Author(s):  
VELJKO POTKONJAK
Keyword(s):  
Mathematical Models ◽  
Muscle Fatigue ◽  
Simulation Study ◽  
Robot Control ◽  
Robot Arm ◽  
Redundancy Resolution ◽  
Kinematic Redundancy ◽  
New Concepts ◽  
Human Arm ◽  
Arm Motion

Handwriting has always been considered an important human task, and accordingly it has attracted the attention of researchers working in biomechanics, physiology, and related fields. There exist a number of studies on this area. This paper considers the human–machine analogy and relates robots with handwriting. The work is two-fold: it improves the knowledge in biomechanics of handwriting, and introduces some new concepts in robot control. The idea is to find the biomechanical principles humans apply when resolving kinematic redundancy, express the principles by means of appropriate mathematical models, and then implement them in robots. This is a step forward in the generation of human-like motion of robots. Two approaches to redundancy resolution are described: (i) "Distributed Positioning" (DP) which is based on a model to represent arm motion in the absence of fatigue, and (ii) the "Robot Fatigue" approach, where robot movements similar to the movements of a human arm under muscle fatigue are generated. Both approaches are applied to a redundant anthropomorphic robot arm performing handwriting. The simulation study includes the issues of legibility and inclination of handwriting. The results demonstrate the suitability and effectiveness of both approaches.

Robot Trajectory Planning Using Rational Frenet-Serret Curves

Volume 2 ◽  
2004 ◽  
Author(s):  
Reza Ravani ◽  
Ali Meghdari
Keyword(s):  
Trajectory Planning ◽  
Computer Animation ◽  
Rational Curves ◽  
Robot Arm ◽  
Robot Trajectory ◽  
Arm Motion ◽  
Sweep Surface ◽  
And Robotics ◽  
Rotation Minimizing Frame ◽  
Robot Trajectory Planning

The aim of this paper is to demonstrate that the techniques of Computer Aided Geometric Design such as spatial rational curves and surfaces could be applied to Kinematics, Computer Animation and Robotics. For this purpose we represent a method which utilizes a special class of rational curves called Rational Frenet-Serret (RF) [8] curves for robot trajectory planning. RF curves distinguished by the property that the motion of their Frenet-Serret frame is rational. We describe an algorithm for interpolation of positions by a rational Frenet-Serret motion. Further more we provide an analysis on spatial frames (Frenet-Serret frame and Rotation Minimizing frame) for smooth robot arm motion and investigate their applications in sweep surface modeling.

scholarly journals Use of Multiple Bacteriophage-Based Structural Color Sensors to Improve Accuracy for Discrimination of Geographical Origins of Agricultural Products

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 986
Author(s):  
Daun Seol ◽  
Daeil Jang ◽  
Kyungjoon Cha ◽  
Jin-Woo Oh ◽  
Hoeil Chung
Keyword(s):  
Agricultural Products ◽  
Support Vector ◽  
Amino Acid Residues ◽  
Discrimination Accuracy ◽  
M13 Bacteriophage ◽  
Color Changes ◽  
Color Sensor ◽  
Improve Accuracy ◽  
Color Sensors ◽  
Unique Individual

A single M13 bacteriophage color sensor was previously utilized for discriminating the geographical origins of agricultural products (garlic, onion, and perilla). The resulting discrimination accuracy was acceptable, ranging from 88.6% to 94.0%. To improve the accuracy further, the use of three separate M13 bacteriophage color sensors containing different amino acid residues providing unique individual color changes (Wild sensor: glutamic acid (E)-glycine (G)-aspartic acid (D), WHW sensor: tryptophan (W)-histidine (H)-tryptophan (W), 4E sensor: four repeating glutamic acids (E)) was proposed. This study was driven by the possibility of enhancing sample discrimination by combining mutually characteristic and complimentary RGB signals obtained from each color sensor, which resulted from dissimilar interactions of sample odors with the employed color sensors. When each color sensor was used individually, the discrimination accuracy based on support vector machine (SVM) ranged from 91.8–94.0%, 88.6–90.3%, and 89.8–92.1% for garlic, onion, and perilla samples, respectively. Accuracy improved to 98.0%, 97.5%, and 97.1%, respectively, by integrating all of the RGB signals acquired from the three color sensors. Therefore, the proposed strategy was effective for improving sample discriminability. To further examine the dissimilar responses of each color sensor to odor molecules, typical odor components in the samples (allyl disulfide, allyl methyl disulfide, and perillaldehyde) were measured using each color sensor, and differences in RGB signals were analyzed.

scholarly journals Design of System for Determining Corn Seed Color Quality Standards using the Fuzzy Logic Method through the Localhost Network

2019 ◽  
Vol 8 (1) ◽  
pp. 62-70
Author(s):  
Reksa Nirvana Alam
Keyword(s):  
Fuzzy Logic ◽  
Seed Quality ◽  
Large Diameter ◽  
Quality Standards ◽  
Quality Standard ◽  
Seed Color ◽  
Accuracy Rate ◽  
Corn Seed ◽  
Color Sensor ◽  
Color Sensors

Control of quality standards is very important role in ensuring corn on the market. Corn seed quality standards are determined from the results of  classification process applied. So far, evaluation process of classification of corn seeds quality is still done manually which takes a long time and the quality of product is'nt evenly distributed. So, we need a tool to determine corn seeds quality to improve its quality. This study conducted color readings of corn seeds using  TCS230 color sensors and sorting  diameter of corn seeds using a small, medium, and large diameter sieve machine. The method for classifying quality standard of corn seed color uses fuzzy logic. The test was carried out by taking data from 3 TCS230 color sensors on each diameter of the sieve machine for corn seeds types used are BISI-2 and BIMA-19. The sensor accuracy is known by comparing data from sensor with data from Color Grab application. The reading results of BISI-2 on the color sensor-1 shows an accuracy rate of 0.3%, the color sensor-2 shows an accuracy rate of 0.72%, and the color sensor-3 shows an accuracy rate of 1.76%. For BIMA-19 corn seeds, the reading on color sensor-1 shows an accuracy of 1.11%, the color sensor-2 shows an accuracy of 24.6%, the color sensor-3 shows an accuracy of 1.10%. The results of fuzzy testing on BISI-2 and BIMA-19 showed that quality standard of maize seeds was good at medium and large diameters, while those on small diameters showed poor quality standards.

Development of Wire Actuated Monolithic Soft Gripper Positioned by Robot Manipulator

2020 ◽  
Author(s):  
Rafael Barreto Gutierrez ◽  
Martin Garcia ◽  
Joan McDuffie ◽  
Courtney Long ◽  
Ayse Tekes
Keyword(s):  
Robot Manipulator ◽  
Compliant Mechanism ◽  
Experimental Testing ◽  
Service Robot ◽  
Servo Motor ◽  
Single Piece ◽  
Pick And Place ◽  
Grasping Force ◽  
3D Printed ◽  
The Right

Abstract This paper presents the design and development of a two fingered, monolithically designed compliant gripper mounted on a two-link robot. Rigid grippers traditionally designed by rigid links and joints might have low precision due to friction and backlash. The proposed gripper is designed as a single piece compliant mechanism consisted of several flexible links and actuated by wire through a servo motor. The gripper is attached to a two-link arm robot driven by three step motors. An additional servo motor can also rotate the base of the robot. While the robot is 3D printed using polylactic acid (PLA), the gripper is 3D printed in thermoplasticpolyurethane (TPU). Two force sensors are attached to the right and left ends of the gripper to measure grasping force. Experimental testing for grasping various objects having different sizes, shapes and weights is carried out to verify the robust performance of the proposed design. Through the experimentation, it’s been noted that the compliant gripper can successfully lift up objects at a maximum mass of 200 g and have a better performance if the objects’width is closer to the width of the gripper. The presented mechanism can be utilized as a service robot for elderly people to assist them pick and place objects or lift objects if equipped with necessary sensors.

scholarly journals Stereo Vision-Based Object Recognition and Manipulation by Regions with Convolutional Neural Network

Electronics ◽  
2020 ◽  
Vol 9 (2) ◽  
pp. 210 ◽  
Author(s):  
Yi-Chun Du ◽  
Muslikhin Muslikhin ◽  
Tsung-Han Hsieh ◽  
Ming-Shyan Wang
Keyword(s):  
Neural Network ◽  
Object Recognition ◽  
Convolutional Neural Network ◽  
Stereo Vision ◽  
Fuzzy Inference ◽  
Target Object ◽  
Robot Arm ◽  
Segmentation Method ◽  
Inference System ◽  
Six Degree Of Freedom

This paper develops a hybrid algorithm of adaptive network-based fuzzy inference system (ANFIS) and regions with convolutional neural network (R-CNN) for stereo vision-based object recognition and manipulation. The stereo camera at an eye-to-hand configuration firstly captures the image of the target object. Then, the shape, features, and centroid of the object are estimated. Similar pixels are segmented by the image segmentation method, and similar regions are merged through selective search. The eye-to-hand calibration is based on ANFIS to reduce computing burden. A six-degree-of-freedom (6-DOF) robot arm with a gripper will conduct experiments to demonstrate the effectiveness of the proposed system.

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