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.

scholarly journals The future of industry with collaborative robots

2019 ◽  
Vol 299 ◽  
pp. 02008 ◽  
Author(s):  
Miriam Matúšová ◽  
Marcela Bučányová ◽  
Erika Hrušková
Keyword(s):  
Quality Of Life ◽  
Production Process ◽  
Large Range ◽  
Industrial Robot ◽  
Industrial Robots ◽  
User Requirements ◽  
Collaborative Robots ◽  
The Future ◽  
Collaborative Robot

Rapidly changing user requirements, improving of quality of life or increased safety at work are allarguments for introducing flexible automation that replaces strenuous or dangerous work. Industrial robots with adaptive directing are now deployed to most industries due to their large range of uses. Theirmain addition for manufacturing is to eliminate downtime of complete operating and manipulating production process, to make easier all particular operation in accordance with ergonomics. The paper describescomparing between conventional industrial robot and collaborative robot.

scholarly journals Force Control Improvement in Collaborative Robots through Theory Analysis and Experimental Endorsement

2020 ◽  
Vol 10 (12) ◽  
pp. 4329 ◽  
Author(s):  
Rodrigo Pérez-Ubeda ◽  
Ranko Zotovic-Stanisic ◽  
Santiago C. Gutiérrez
Keyword(s):  
Force Control ◽  
Industrial Robot ◽  
Good Alternative ◽  
Theory Analysis ◽  
Collaborative Robots ◽  
Loop Control ◽  
Robot Controller ◽  
Different Types ◽  
Collaborative Robot ◽  
Jacobian Inverse

Due to the elasticity of their joints, collaborative robots are seldom used in applications with force control. Besides, the industrial robot controllers are closed and do not allow the user to access the motor torques and other parameters, hindering the possibility of carrying out a customized control. A good alternative to achieve a custom force control is sending the output of the force regulator to the robot controller through motion commands (inner/outer loop control). There are different types of motion commands (e.g., position or velocity). They may be implemented in different ways (Jacobian inverse vs. Jacobian transpose), but this information is usually not available for the user. This article is dedicated to the analysis of the effect of different inner loops and their combination with several external controllers. Two of the most determinant factors found are the type of the inner loop and the stiffness matrix. The theoretical deductions have been experimentally verified on a collaborative robot UR3, allowing us to choose the best behaviour in a polishing operation according to pre-established criteria.

A Polishing Robot Force Control System Based on Time Series Data in Industrial Internet of Things

2021 ◽  
Vol 21 (2) ◽  
pp. 1-22
Author(s):  
Chen Zhang ◽  
Zhuo Tang ◽  
Kenli Li ◽  
Jianzhong Yang ◽  
Li Yang
Keyword(s):  
Time Series ◽  
Control System ◽  
Force Control ◽  
Time Series Data ◽  
Industrial Robot ◽  
Industrial Robots ◽  
Series Data ◽  
Industrial Internet Of Things ◽  
Industrial Internet ◽  
Force Control System

Installing a six-dimensional force/torque sensor on an industrial arm for force feedback is a common robotic force control strategy. However, because of the high price of force/torque sensors and the closedness of an industrial robot control system, this method is not convenient for industrial mass production applications. Various types of data generated by industrial robots during the polishing process can be saved, transmitted, and applied, benefiting from the growth of the industrial internet of things (IIoT). Therefore, we propose a constant force control system that combines an industrial robot control system and industrial robot offline programming software for a polishing robot based on IIoT time series data. The system mainly consists of four parts, which can achieve constant force polishing of industrial robots in mass production. (1) Data collection module. Install a six-dimensional force/torque sensor at a manipulator and collect the robot data (current series data, etc.) and sensor data (force/torque series data). (2) Data analysis module. Establish a relationship model based on variant long short-term memory which we propose between current time series data of the polishing manipulator and data of the force sensor. (3) Data prediction module. A large number of sensorless polishing robots of the same type can utilize that model to predict force time series. (4) Trajectory optimization module. The polishing trajectories can be adjusted according to the prediction sequences. The experiments verified that the relational model we proposed has an accurate prediction, small error, and a manipulator taking advantage of this method has a better polishing effect.

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 Suppress Vibration on Robotic Polishing with Impedance Matching

Actuators ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 59
Author(s):  
Junjie Dai ◽  
Chin-Yin Chen ◽  
Renfeng Zhu ◽  
Guilin Yang ◽  
Chongchong Wang ◽  
...  
Keyword(s):  
Contact Force ◽  
Force Control ◽  
Impedance Control ◽  
Impedance Matching ◽  
Industrial Robots ◽  
Contact Phase ◽  
Dynamic Tracking ◽  
Force Tracking ◽  
The Difference ◽  
End Effectors

Installing force-controlled end-effectors on the end of industrial robots has become the mainstream method for robot force control. Additionally, during the polishing process, contact force stability has an important impact on polishing quality. However, due to the difference between the robot structure and the force-controlled end-effector, in the polishing operation, direct force control will have impact during the transition from noncontact to contact between the tool and the workpiece. Although impedance control can solve this problem, industrial robots still produce vibrations with high inertia and low stiffness. Therefore, this research proposes an impedance matching control strategy based on traditional direct force control and impedance control methods to improve this problem. This method’s primary purpose is to avoid force vibration in the contact phase and maintain force–tracking performance during the dynamic tracking phase. Simulation and experimental results show that this method can smoothly track the contact force and reduce vibration compared with traditional force control and impedance control.

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.

scholarly journals Morphology of <i>Emiliania huxleyi</i> coccoliths on the North West European shelf – is there an influence of carbonate chemistry?

2014 ◽  
Vol 11 (3) ◽  
pp. 4531-4561 ◽  
Author(s):  
J. R. Young ◽  
A. J. Poulton ◽  
T. Tyrrell
Keyword(s):  
Environmental Samples ◽  
Significant Variation ◽  
Emiliania Huxleyi ◽  
Morphometric Study ◽  
Saturation State ◽  
North West ◽  
The North ◽  
Microscope Images ◽  
Calcite Saturation ◽  
The Uk

Abstract. Within the context of the UK Ocean Acidification project, Emiliania huxleyi (type A) coccolith morphology was examined from samples collected during cruise D366. In particular, a morphometric study of coccolith size and degree of calcification was made on scanning electron microscope images of samples from shipboard CO2 perturbation experiments and from a set of environmental samples with significant variation in calcite saturation state (Ωcalcite). One bioassay in particular (E4 from the southern North Sea) yielded unambiguous results – in this bioassay exponential growth from a low level occurred with no artificial stimulation and coccosphere numbers increased ten-fold during the experiment. The samples with elevated CO2 saw significantly reduced coccolithophore growth. However, coccolithophore morphology was not significantly affected by the changing CO2 conditions even under the highest levels of perturbation (1000 μatm). Environmental samples similarly showed no correlation of coccolithophore morphology with calcite saturation state. Some variation in coccolith size and degree of calcification does occur but this seems to be predominantly due to genotypic differentiation between populations on the shelf and in the open ocean.

scholarly journals Human-Following Motion Planning and Control Scheme for Collaborative Robots Based on Human Motion Prediction

2021 ◽  
Author(s):  
Fahad Iqbal Khawaja ◽  
Akira Kanazawa ◽  
Jun Kinugawa ◽  
Kazuhiro Kosuge
Keyword(s):  
Motion Planning ◽  
Human Motion ◽  
Human Robot Interaction ◽  
Collaborative Robots ◽  
Sensing System ◽  
Planning And Control ◽  
Control Scheme ◽  
Active Research ◽  
And Control ◽  
Collaborative Robot

Human-Robot Interaction (HRI) for collaborative robots has become an active research topic recently. Collaborative robots assist the human workers in their tasks and improve their efficiency. But the worker should also feel safe and comfortable while interacting with the robot. In this paper, we propose a human-following motion planning and control scheme for a collaborative robot which supplies the necessary parts and tools to a worker in an assembly process in a factory. In our proposed scheme, a 3-D sensing system is employed to measure the skeletal data of the worker. At each sampling time of the sensing system, an optimal delivery position is estimated using the real-time worker data. At the same time, the future positions of the worker are predicted as probabilistic distributions. A Model Predictive Control (MPC) based trajectory planner is used to calculate a robot trajectory that supplies the required parts and tools to the worker and follows the predicted future positions of the worker. We have installed our proposed scheme in a collaborative robot system with a 2-DOF planar manipulator. Experimental results show that the proposed scheme enables the robot to provide anytime assistance to a worker who is moving around in the workspace while ensuring the safety and comfort of the worker.

scholarly journals Povećana sigurnost radnika primjenom kolaborativnih robota u proizvodnim procesima Industrije 4.0

Sigurnost ◽  
2020 ◽  
Vol 62 (1) ◽  
pp. 11-18
Author(s):  
Isak Karabegović ◽  
Edina Karabegović
Keyword(s):  
First Generation ◽  
Industrial Revolution ◽  
Industrial Robots ◽  
Smart Manufacturing ◽  
Medium Size ◽  
Collaborative Robots ◽  
Production Processes ◽  
Working Together ◽  
Levels Of Automation ◽  
Complete Automation

SUMMARY: By applying Industry 4.0, modernization of the production processes in industry is achieved. However, the safety of workers must be a priority. Automation of production processes and raising it to a higher level can be achieved by employing collaborative robots working together with workers. The degree of safety measures guarantees that there are no work injuries. In using collaborative robots we exploit all the advantages that they possess over first-generation industrial robots. They work together with workers, workers work in a safe environment, robots take up less space, they are not physically separated from workers, they are easy to manipulate, they are cheaper, and are suitable for small and medium size companies. We have the possibility of introducing different levels of automation in the production process, i.e. we can partially automate the tasks where complete automation is too complex or not economical. The use of collaborative robots will grow in the future, since the goals of the fourth industrial revolution cannot be achieved without collaborative robots, in other words, without the "smart manufacturing process" or "smart factory".

Sign in / Sign up

Export Citation Format

Share Document