scholarly journals IMPROVING HUMAN AWARENESS DURING COLLABORATION WITH ROBOT: REVIEW

2021 ◽  
Vol 2021 (6) ◽  
pp. 5475-5480
Author(s):  
STEFAN GRUSHKO ◽  
◽  
ALES VYSOCKY ◽  
JIRI SUDER ◽  
LADISLAV GLOGAR ◽  
...  
Keyword(s):  
Industry 4.0 ◽  
Haptic Feedback ◽  
Industrial Applications ◽  
Task Completion ◽  
Current Position ◽  
Manufacturing Automation ◽  
Robot Trajectory ◽  
Human Robot Collaboration ◽  
Collaborative Robot ◽  
Human Awareness

Human-robot collaboration is a widespread topic within the concept of Industry 4.0. Such collaboration brings new opportunities to improve ergonomics and innovative options for manufacturing automation; however, most of the modern collaborative industrial applications are limited by the fact that neither collaborative side is fully aware of the partner: the human operator may not see the robot movement due to own engagement in the work process, and the collaborative robot simply has no means of knowing the position of the operator. Dynamic replanning of the robot trajectory with respect to the operator's current position can increase the efficiency and safety of cooperation since the robot will be able to avoid collisions and proceed in task completion; however, the other side of communication remains unresolved. This paper provides a review of methods of improving human awareness during collaboration with a robot. Covered techniques include graphical, acoustic and haptic feedback implementations. The work is focused on the practical applicability of the approaches, and analyses present challenges associated with each method.

Telepresence in Industrial Applications: Implementation Issues for Assembly Tasks

2010 ◽  
Vol 19 (5) ◽  
pp. 415-429 ◽  
Author(s):  
Marwan Radi ◽  
Verena Nitsch
Keyword(s):  
Force Feedback ◽  
Haptic Feedback ◽  
Industrial Applications ◽  
Task Completion ◽  
Human Intelligence ◽  
Guidance Strategies ◽  
Industrial Setting ◽  
Successful Execution ◽  
Place Task ◽  
Assembly Tasks

In contrast to automated production, human intelligence is deemed necessary for successful execution of assembly tasks that are difficult or expensive to automate in small and medium lots. However, human ability is hindered in some cases by physical barriers such as miniaturization or in contrast, very heavy components. Telepresence technology can be considered a solution for performing a wide variety of assembly tasks where human intelligence and haptic sense are needed. This work highlights several issues involved in deploying industrial telepresence systems to manipulate and assemble microparts as well as heavy objects. Two sets of experiments are conducted to investigate telepresence related aspects in an industrial setting. The first experiment evaluates the usefulness of haptic feedback for a human operator in a standard pick-and-place task. Three operation modes were considered: visual feedback, force feedback, and force assistance (realized as vibration). In the second experiment, two different guidance strategies for the teleoperator were tested. The comparison between a position and a velocity scheme in terms of task completion time and subjective preferences is presented.

scholarly journals Intuitive Spatial Tactile Feedback for Better Awareness about Robot Trajectory during Human–Robot Collaboration

Sensors ◽  
2021 ◽  
Vol 21 (17) ◽  
pp. 5748
Author(s):  
Stefan Grushko ◽  
Aleš Vysocký ◽  
Dominik Heczko ◽  
Zdenko Bobovský
Keyword(s):  
User Study ◽  
Haptic Feedback ◽  
Spatial Configuration ◽  
Tactile Feedback ◽  
Coordinate Frame ◽  
Subjective Data ◽  
Directional Information ◽  
Notification System ◽  
Robot Trajectory ◽  
Human Robot Collaboration

In this work, we extend the previously proposed approach of improving mutual perception during human–robot collaboration by communicating the robot’s motion intentions and status to a human worker using hand-worn haptic feedback devices. The improvement is presented by introducing spatial tactile feedback, which provides the human worker with more intuitive information about the currently planned robot’s trajectory, given its spatial configuration. The enhanced feedback devices communicate directional information through activation of six tactors spatially organised to represent an orthogonal coordinate frame: the vibration activates on the side of the feedback device that is closest to the future path of the robot. To test the effectiveness of the improved human–machine interface, two user studies were prepared and conducted. The first study aimed to quantitatively evaluate the ease of differentiating activation of individual tactors of the notification devices. The second user study aimed to assess the overall usability of the enhanced notification mode for improving human awareness about the planned trajectory of a robot. The results of the first experiment allowed to identify the tactors for which vibration intensity was most often confused by users. The results of the second experiment showed that the enhanced notification system allowed the participants to complete the task faster and, in general, improved user awareness of the robot’s movement plan, according to both objective and subjective data. Moreover, the majority of participants (82%) favoured the improved notification system over its previous non-directional version and vision-based inspection.

Challenges and opportunities in human robot collaboration context of Industry 4.0 - a state of the art review

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Anil Kumar Inkulu ◽  
M.V.A. Raju Bahubalendruni ◽  
Ashok Dara ◽  
SankaranarayanaSamy K.
Keyword(s):  
Mass Customization ◽  
Industry 4.0 ◽  
Research Literature ◽  
Human Robot Interaction ◽  
Relevant Research ◽  
Robot Interaction ◽  
Content Type ◽  
Manufacturing Automation ◽  
Challenges And Opportunities ◽  
Human Robot Collaboration

Purpose In the present era of Industry 4.0, the manufacturing automation is moving toward mass production and mass customization through human–robot collaboration. The purpose of this paper is to describe various human–robot collaborative (HRC) techniques and their applicability for various manufacturing methods along with key challenges. Design/methodology/approach Numerous recent relevant research literature has been analyzed, and various human–robot interaction methods have been identified, and detailed discussions are made on one- and two-way human–robot collaboration. Findings The challenges in implementing human–robot collaboration for various manufacturing process and the challenges in one- and two-way collaboration between human and robot are found and discussed. Originality/value The authors have attempted to classify the HRC techniques and demonstrated the challenges in different modes.

Collaborative Robot Risk of Passage Among Dynamic Obstacles

2021 ◽  
Author(s):  
Jared T. Flowers ◽  
Gloria J. Wiens
Keyword(s):  
Industry 4.0 ◽  
Material Handling ◽  
Future Time ◽  
Cycle Times ◽  
Robot Trajectory ◽  
Collaborative Interactions ◽  
Collaborative Robot ◽  
Smart Factories ◽  
Factories Of The Future ◽  
Novel Algorithm

Abstract Industry 4.0 projects ubiquitous collaborative robots in smart factories of the future, particularly in assembly and material handling. To ensure efficient and safe human-robot collaborative interactions, this paper presents a novel algorithm for estimating Risk of Passage (ROP) a robot incurs by passing between dynamic obstacles (humans, moving equipment, etc.). This paper posits that robot trajectory durations will be shorter and safer if the robot can react proactively to predicted collision between a robot and human worker before it occurs, compared to reacting when it is imminent. I.e., if the risk that obstacles may prohibit robot passage at a future time in the robot’s trajectory is greater than a user defined risk limit, then an Obstacle Pair Volume (OPV), encompassing the obstacles at that time, is added to the planning scene. Results found from simulation show that an ROP algorithm can be trained in ∼120 workcell cycles. Further, it is demonstrated that when a trained ROP algorithm introduces an OPV, trajectory durations are shorter compared to those avoiding obstacles without the introduction of an OPV. The use of ROP estimation with addition of OPV allows workcells to operate proactively smoother with shorter cycle times in the presence of unforeseen obstacles.

scholarly journals Special Issue of the Manufacturing Engineering Society 2020 (SIMES-2020)

2021 ◽  
Vol 11 (13) ◽  
pp. 5975
Author(s):  
Ana María Camacho ◽  
Eva María Rubio
Keyword(s):  
Applied Sciences ◽  
Modeling And Simulation ◽  
Industry 4.0 ◽  
Product Lifecycle Management ◽  
Special Issue ◽  
Product Lifecycle ◽  
Manufacturing Automation ◽  
Engineering Society ◽  
Manufacturing Engineering ◽  
Lifecycle Management

The Special Issue of the Manufacturing Engineering Society 2020 (SIMES-2020) has been launched as a joint issue of the journals “Materials” and “Applied Sciences”. The 14 contributions published in this Special Issue of Applied Sciences present cutting-edge advances in the field of Manufacturing Engineering focusing on advances and innovations in manufacturing processes; additive manufacturing and 3D printing; manufacturing of new materials; Product Lifecycle Management (PLM) technologies; robotics, mechatronics and manufacturing automation; Industry 4.0; design, modeling and simulation in manufacturing engineering; manufacturing engineering and society; and production planning. Among them, the topic “Manufacturing engineering and society” collected the highest number of contributions (representing 22%), followed by the topics “Product Lifecycle Management (PLM) technologies”, “Industry 4.0”, and “Design, modeling and simulation in manufacturing engineering” (each at 14%). The rest of the topics represent the remaining 35% of the contributions.

scholarly journals Improved Mutual Understanding for Human-Robot Collaboration: Combining Human-Aware Motion Planning with Haptic Feedback Devices for Communicating Planned Trajectory

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3673
Author(s):  
Stefan Grushko ◽  
Aleš Vysocký ◽  
Petr Oščádal ◽  
Michal Vocetka ◽  
Petr Novák ◽  
...  
Keyword(s):  
User Study ◽  
Haptic Feedback ◽  
Fundamental Aspect ◽  
Task Completion ◽  
Good Efficiency ◽  
Notification System ◽  
Movement Data ◽  
Novel Approach ◽  
Machine Interface ◽  
High Degree

In a collaborative scenario, the communication between humans and robots is a fundamental aspect to achieve good efficiency and ergonomics in the task execution. A lot of research has been made related to enabling a robot system to understand and predict human behaviour, allowing the robot to adapt its motion to avoid collisions with human workers. Assuming the production task has a high degree of variability, the robot’s movements can be difficult to predict, leading to a feeling of anxiety in the worker when the robot changes its trajectory and approaches since the worker has no information about the planned movement of the robot. Additionally, without information about the robot’s movement, the human worker cannot effectively plan own activity without forcing the robot to constantly replan its movement. We propose a novel approach to communicating the robot’s intentions to a human worker. The improvement to the collaboration is presented by introducing haptic feedback devices, whose task is to notify the human worker about the currently planned robot’s trajectory and changes in its status. In order to verify the effectiveness of the developed human-machine interface in the conditions of a shared collaborative workspace, a user study was designed and conducted among 16 participants, whose objective was to accurately recognise the goal position of the robot during its movement. Data collected during the experiment included both objective and subjective parameters. Statistically significant results of the experiment indicated that all the participants could improve their task completion time by over 45% and generally were more subjectively satisfied when completing the task with equipped haptic feedback devices. The results also suggest the usefulness of the developed notification system since it improved users’ awareness about the motion plan of the robot.

scholarly journals Digital industry and manufacturing automation: impact on employment

2020 ◽  
Vol 1 (2) ◽  
pp. 17-19
Author(s):  
Danil Alekseevich Zyukin
Keyword(s):  
Automotive Industry ◽  
Industry 4.0 ◽  
Structural Complexity ◽  
Digital Transformation ◽  
Fourth Generation ◽  
Production Sector ◽  
Manufacturing Automation ◽  
Manufacturing Enterprises ◽  
Systemic Level

The aim of article. The digital industry (Industry 4.0, the fourth-generation industry) is developing - based on the digital transformation of the production sector. Countries must create a workforce ready for future infrastructure. This requires the cooperation of universities, government and industry, including initiatives aimed at training workers for the transforming productive sector. The pandemic has COVID-19 exacerbated the problem of employment. Methodology: it is necessary to study the problem of employment at the systemic level, with an analysis of the structural complexity and development of digital transformations. This article explores this problem for manufacturing enterprises, in particular the automotive industry. The Results and Conclusions present the results of the analysis and make forecasts.

Laser Additive Manufacturing in Industry 4.0

2021 ◽  
pp. 729-754
Author(s):  
Christ P. Paul ◽  
Arackal N. Jinoop ◽  
Saurav K. Nayak ◽  
Alini C. Paul
Keyword(s):  
Additive Manufacturing ◽  
Industry 4.0 ◽  
High Performance ◽  
Industrial Revolution ◽  
Developing Economies ◽  
New Technology ◽  
Industrial Applications ◽  
Laser Additive Manufacturing ◽  
Global Status ◽  
Feature Based Design

Additive manufacturing is one of the nine technologies fuelling the fourth industrial revolution (Industry 4.0). High power lasers augmented with allied digital technologies is changing the entire manufacturing scenario through metal additive manufacturing by providing feature-based design and manufacturing with the technology called laser additive manufacturing (LAM). It enables the fabrication of customized components having complex and lightweight designs with high performance in a short period. The chapter compiles the evolution and global status of LAM technology highlighting its advantages and freedoms for various industrial applications. It discusses how LAM is contributing to Industry 4.0 for the fabrication of customized engineering and prosthetic components through case studies. It compiles research, development, and deployment scenarios of this new technology in developing economies along with the future scope of the technology.

A case study in human–robot collaboration in the disassembly of press-fitted components

2019 ◽  
Vol 234 (3) ◽  
pp. 654-664 ◽  
Author(s):  
Jun Huang ◽  
Duc Truong Pham ◽  
Yongjing Wang ◽  
Mo Qu ◽  
Chunqian Ji ◽  
...  
Keyword(s):  
End Of Life ◽  
Industrial Robot ◽  
New Method ◽  
Water Pump ◽  
Compliance Control ◽  
Critical Step ◽  
Active Compliance ◽  
Human Robot Collaboration ◽  
Collaborative Robot

Human–robot collaborative disassembly is an approach designed to mitigate the effects of uncertainties associated with the condition of end-of-life products returned for remanufacturing. This flexible semi-autonomous approach can also handle unpredictability in the frequency and numbers of such returns as well as variance in the remanufacturing process. This article focusses on disassembly, which is the first and arguably the most critical step in remanufacturing. The article presents a new method for disassembling press-fitted components using human–robot collaboration based on the active compliance provided by a collaborative robot. The article first introduces the concepts of human–robot collaborative disassembly and outlines the method of active compliance control. It then details a case study designed to demonstrate the proposed method. The study involved the disassembly of an automotive water pump by a collaborative industrial robot working with a human operator to take apart components that had been press-fitted together. The results show the feasibility of the proposed method.

Sign in / Sign up

Export Citation Format

Share Document