YuMi, Come and Play with Me! A Collaborative Robot for Piecing Together a Tangram Puzzle

2016 ◽  
pp. 243-251 ◽  
Author(s):  
David Kirschner ◽  
Rosemarie Velik ◽  
Saeed Yahyanejad ◽  
Mathias Brandstötter ◽  
Michael Hofbaur
Keyword(s):  
Collaborative Robot

scholarly journals Simulation of Grasp Localization Inferences for a Dual-Arm Collaborative Robot

2021 ◽  
Vol 1012 ◽  
pp. 012004
Author(s):  
A Josin Hippolitus ◽  
R. Senthilnathan ◽  
Omar Malla
Keyword(s):  
Collaborative Robot ◽  
Dual Arm

scholarly journals CNN Training Using 3D Virtual Models for Assisted Assembly with Mixed Reality and Collaborative Robots

2021 ◽  
Vol 11 (9) ◽  
pp. 4269
Author(s):  
Kamil Židek ◽  
Ján Piteľ ◽  
Michal Balog ◽  
Alexander Hošovský ◽  
Vratislav Hladký ◽  
...  
Keyword(s):  
Mixed Reality ◽  
Current Trend ◽  
Robot Vision ◽  
Processing Unit ◽  
Single Shot ◽  
Vision Systems ◽  
Collaborative Robots ◽  
Training Time ◽  
Position And Orientation ◽  
Collaborative Robot

The assisted assembly of customized products supported by collaborative robots combined with mixed reality devices is the current trend in the Industry 4.0 concept. This article introduces an experimental work cell with the implementation of the assisted assembly process for customized cam switches as a case study. The research is aimed to design a methodology for this complex task with full digitalization and transformation data to digital twin models from all vision systems. Recognition of position and orientation of assembled parts during manual assembly are marked and checked by convolutional neural network (CNN) model. Training of CNN was based on a new approach using virtual training samples with single shot detection and instance segmentation. The trained CNN model was transferred to an embedded artificial processing unit with a high-resolution camera sensor. The embedded device redistributes data with parts detected position and orientation into mixed reality devices and collaborative robot. This approach to assisted assembly using mixed reality, collaborative robot, vision systems, and CNN models can significantly decrease assembly and training time in real production.

scholarly journals Method for Robot Manipulator Joint Wear Reduction by Finding the Optimal Robot Placement in a Robotic Cell

2021 ◽  
Vol 11 (12) ◽  
pp. 5398
Author(s):  
Tomáš Kot ◽  
Zdenko Bobovský ◽  
Aleš Vysocký ◽  
Václav Krys ◽  
Jakub Šafařík ◽  
...  
Keyword(s):  
Angular Velocity ◽  
Dynamic Simulation ◽  
Robot Manipulator ◽  
The Other ◽  
Robotic Arm ◽  
Robotic Cell ◽  
Wear Reduction ◽  
Fixed End ◽  
Robot Placement ◽  
Collaborative Robot

We describe a method for robotic cell optimization by changing the placement of the robot manipulator within the cell in applications with a fixed end-point trajectory. The goal is to reduce the overall robot joint wear and to prevent uneven joint wear when one or several joints are stressed more than the other joints. Joint wear is approximated by calculating the integral of the mechanical work of each joint during the whole trajectory, which depends on the joint angular velocity and torque. The method relies on using a dynamic simulation for the evaluation of the torques and velocities in robot joints for individual robot positions. Verification of the method was performed using CoppeliaSim and a laboratory robotic cell with the collaborative robot UR3. The results confirmed that, with proper robot base placement, the overall wear of the joints of a robotic arm could be reduced from 22% to 53% depending on the trajectory.

scholarly journals Cobot attack: a security assessment exemplified by a specific collaborative robot

2021 ◽  
Vol 54 ◽  
pp. 191-196
Author(s):  
Siegfried Hollerer ◽  
Clara Fischer ◽  
Bernhard Brenner ◽  
Maximilian Papa ◽  
Sebastian Schlund ◽  
...  
Keyword(s):  
Security Assessment ◽  
Collaborative Robot

scholarly journals Behavioural Study of the Force Control Loop Used in a Collaborative Robot for Sanding Materials

Materials ◽  
2020 ◽  
Vol 14 (1) ◽  
pp. 67
Author(s):  
Rodrigo Pérez Ubeda ◽  
Santiago C. Gutiérrez Rubert ◽  
Ranko Zotovic Stanisic ◽  
Ángel Perles Ivars
Keyword(s):  
Force Control ◽  
Feed Rate ◽  
Significant Variation ◽  
Industrial Robots ◽  
Control Loop ◽  
Saturation State ◽  
Collaborative Robots ◽  
Increase Productivity ◽  
Different Characteristics ◽  
Collaborative Robot

The rise of collaborative robots urges the consideration of them for different industrial tasks such as sanding. In this context, the purpose of this article is to demonstrate the feasibility of using collaborative robots in processing operations, such as orbital sanding. For the demonstration, the tools and working conditions have been adjusted to the capacity of the robot. Materials with different characteristics have been selected, such as aluminium, steel, brass, wood, and plastic. An inner/outer control loop strategy has been used, complementing the robot’s motion control with an outer force control loop. After carrying out an explanatory design of experiments, it was observed that it is possible to perform the operation in all materials, without destabilising the control, with a mean force error of 0.32%. Compared with industrial robots, collaborative ones can perform the same sanding task with similar results. An important outcome is that unlike what might be thought, an increase in the applied force does not guarantee a better finish. In fact, an increase in the feed rate does not produce significant variation in the finish—less than 0.02 µm; therefore, the process is in a “saturation state” and it is possible to increase the feed rate to increase productivity.

Europe continues to lead the way in the collaborative robot business

2016 ◽  
Vol 43 (1) ◽  
pp. 6-11 ◽  
Author(s):  
Robert Bogue
Keyword(s):  
Automotive Industry ◽  
Market Development ◽  
Future Market ◽  
Collaborative Robots ◽  
Content Type ◽  
Production Methods ◽  
Research Activities ◽  
Timely Review ◽  
New Applications ◽  
Collaborative Robot

Purpose – This paper aims to provide a European perspective on the collaborative robot business and to consider the factors governing future market development. Design/methodology/approach – Following an introduction, this first describes the collaborative robots launched recently by European manufacturers and their applications. It then discusses major European research activities and finally considers the factors stimulating the market. Findings – This article shows that collaborative robots are being commercialised by the major European robot manufacturers as well as by several smaller specialists. Although most have low payload capacities they are inexpensive and offer a number of operational benefits, making them well suited to a range of existing and emerging applications. Europe has a strong research base and several EU-funded programmes aim to stimulate collaborative robot development and use. Rapid market development is anticipated, driven in the main by applications in electronic product manufacture and assembly; new applications in the automotive industry; uses by small to medium-sized manufacturers; and companies seeking robots to support agile production methods. Originality/value – This paper provides a timely review of the rapidly developing European collaborative robot industry.

Zero Moment Control for Lead-Through Teach Programming on a Collaborative Robot

2021 ◽  
Author(s):  
Stephen Canfield ◽  
Joseph Owens ◽  
Stephen Zuccaro
Keyword(s):  
Moment Control ◽  
Zero Moment ◽  
Collaborative Robot
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