Low-Cost Vision System for Pick and Place application using camera and ABB Industrial Robot

Author(s):  
Saurabh Chakole ◽  
Neema Ukani
2018 ◽  
Vol 10 (4) ◽  
Author(s):  
Chih-Hsing Liu ◽  
Chen-Hua Chiu ◽  
Ta-Lun Chen ◽  
Tzu-Yang Pai ◽  
Mao-Cheng Hsu ◽  
...  

This study presents a topology optimization method to synthesize an innovative compliant finger for grasping objects with size and shape variations. The design domain of the compliant finger is a trapezoidal area with one input and two output ports. The topology optimized finger design is prototyped by three-dimensional (3D) printing using flexible filament, and be used in the developed gripper module, which consists of one actuator and two identical compliant fingers. Both fingers are actuated by one displacement input, and can grip objects through elastic deformation. The gripper module is mounted on an industrial robot to pick and place a variety of objects to demonstrate the effectiveness of the proposed design. The results show that the developed compliant finger can be used to handle vulnerable objects without causing damage to the surface of grasped items. The proposed compliant finger is a monolithic and low-cost design, which can be used to resolve the challenge issue for robotic automation of irregular and vulnerable objects.


Author(s):  
Xiaowen Yu ◽  
Yu Zhao ◽  
Masayoshi Tomizuka

In glass manufacturing industry, glass grinding process has significant involvement of human workers. Human workers need to load and unload glass pieces to/from the grinder. A 6 DOF industrial robot could be used to automate the process by the “pick and place” task. In this paper, a vision system is implemented to robustly detect glass piece location and the placing destination. Two distinct detection methods are used for different glass settings. A “pick and place” trajectory is automatically generated based on the detected locations. A simulation is first performed to visualize robot motion before operating on the robot.


2020 ◽  
Vol 4 (2) ◽  
pp. 48-55
Author(s):  
A. S. Jamaludin ◽  
M. N. M. Razali ◽  
N. Jasman ◽  
A. N. A. Ghafar ◽  
M. A. Hadi

The gripper is the most important part in an industrial robot. It is related with the environment around the robot. Today, the industrial robot grippers have to be tuned and custom made for each application by engineers, by searching to get the desired repeatability and behaviour. Vacuum suction is one of the grippers in Watch Case Press Production (WCPP) and a mechanism to improve the efficiency of the manufacturing procedure. Pick and place are the important process for the annealing process. Thus, by implementing vacuum suction gripper, the process of pick and place can be improved. The purpose of vacuum gripper other than design vacuum suction mechanism is to compare the effectiveness of vacuum suction gripper with the conventional pick and place gripper. Vacuum suction gripper is a mechanism to transport part and which later sequencing, eliminating and reducing the activities required to complete the process. Throughout this study, the process pick and place became more effective, the impact on the production of annealing process is faster. The vacuum suction gripper can pick all part at the production which will lower the loss of the productivity. In conclusion, vacuum suction gripper reduces the cycle time about 20%. Vacuum suction gripper can help lower the cycle time of a machine and allow more frequent process in order to increase the production flexibility.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Supakorn Harnsoongnoen ◽  
Nuananong Jaroensuk

AbstractThe water displacement and flotation are two of the most accurate and rapid methods for grading and assessing freshness of agricultural products based on density determination. However, these techniques are still not suitable for use in agricultural inspections of products such as eggs that absorb water which can be considered intrusive or destructive and can affect the result of measurements. Here we present a novel proposal for a method of non-destructive, non-invasive, low cost, simple and real—time monitoring of the grading and freshness assessment of eggs based on density detection using machine vision and a weighing sensor. This is the first proposal that divides egg freshness into intervals through density measurements. The machine vision system was developed for the measurement of external physical characteristics (length and breadth) of eggs for evaluating their volume. The weighing system was developed for the measurement of the weight of the egg. Egg weight and volume were used to calculate density for grading and egg freshness assessment. The proposed system could measure the weight, volume and density with an accuracy of 99.88%, 98.26% and 99.02%, respectively. The results showed that the weight and freshness of eggs stored at room temperature decreased with storage time. The relationship between density and percentage of freshness was linear for the all sizes of eggs, the coefficient of determination (R2) of 0.9982, 0.9999, 0.9996, 0.9996 and 0.9994 for classified egg size classified 0, 1, 2, 3 and 4, respectively. This study shows that egg freshness can be determined through density without using water to test for water displacement or egg flotation which has future potential as a measuring system important for the poultry industry.


Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 343
Author(s):  
Kim Bjerge ◽  
Jakob Bonde Nielsen ◽  
Martin Videbæk Sepstrup ◽  
Flemming Helsing-Nielsen ◽  
Toke Thomas Høye

Insect monitoring methods are typically very time-consuming and involve substantial investment in species identification following manual trapping in the field. Insect traps are often only serviced weekly, resulting in low temporal resolution of the monitoring data, which hampers the ecological interpretation. This paper presents a portable computer vision system capable of attracting and detecting live insects. More specifically, the paper proposes detection and classification of species by recording images of live individuals attracted to a light trap. An Automated Moth Trap (AMT) with multiple light sources and a camera was designed to attract and monitor live insects during twilight and night hours. A computer vision algorithm referred to as Moth Classification and Counting (MCC), based on deep learning analysis of the captured images, tracked and counted the number of insects and identified moth species. Observations over 48 nights resulted in the capture of more than 250,000 images with an average of 5675 images per night. A customized convolutional neural network was trained on 2000 labeled images of live moths represented by eight different classes, achieving a high validation F1-score of 0.93. The algorithm measured an average classification and tracking F1-score of 0.71 and a tracking detection rate of 0.79. Overall, the proposed computer vision system and algorithm showed promising results as a low-cost solution for non-destructive and automatic monitoring of moths.


1983 ◽  
Vol 16 (20) ◽  
pp. 337-341
Author(s):  
V.M. Grishkin ◽  
F.M. Kulakov

2012 ◽  
Vol 11 (3) ◽  
pp. 9-17 ◽  
Author(s):  
Sébastien Kuntz ◽  
Ján Cíger

A lot of professionals or hobbyists at home would like to create their own immersive virtual reality systems for cheap and taking little space. We offer two examples of such "home-made" systems using the cheapest hardware possible while maintaining a good level of immersion: the first system is based on a projector (VRKit-Wall) and cost around 1000$, while the second system is based on a head-mounted display (VRKit-HMD) and costs between 600� and 1000�. We also propose a standardization of those systems in order to enable simple application sharing. Finally, we describe a method to calibrate the stereoscopy of a NVIDIA 3D Vision system.


2019 ◽  
Vol 6 (12) ◽  
pp. 398-400
Author(s):  
Rodrigo Barbosa Tudeschini ◽  
Raphael Barbosa Carneiro de Lima ◽  
Luiz Flavio Martins Pereira ◽  
Álvaro Manoel de Souza Soares

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