Collaborative Robots and Industrial Revolution 4.0 (IR 4.0)

Sherwani, Fahad; Asad, Muhammad Mujtaba; Ibrahim, Badaruddin

doi:10.1109/icetst49965.2020.9080724

Cited by 146 publications

(81 citation statements)

References 11 publications

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“…Collaborative robotics has become one of the fastest-growing sectors of the robotics markets. If cobots is the key technology for the advancement of Industry 4.0 (Sherwani et al, 2020), it is also a burgeoning technology sector in its own right. Statzon market intelligence data utilised for this article shows that the global cobot market was already estimated to be at around $1.3 billion in 2020, with a CAGR of almost 40% until 2028 to a total worldwide market size of $16.5 billion.…”

Section: Resultsmentioning

confidence: 99%

Market Structure analysis with Herfindahl-Hirchman Index and Lauraéus-Kaivo-Oja Indices in the Global Cobotics Markets

Lauraéus

Kaivo‐oja

Knudsen

et al. 2021

Economics and Culture

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Research purpose. The study is focused on the expected market dynamics of global cobotics markets. This study investigates the current market structure of the global cobotics market. The scientific aim of the research is to report the first data-based market structure analysis of the global cobotics market with the HHI index and with the LKI index analysis. With analysis we are able to show the diversification rate of the global cobotics market. Design / Methodology / Approach. The methodology is based on conventional statistical index theory and statistics. The methodology is the calculation of the Herfindahl-Hirchman Index and the Lauraéus-Kaivo-oja Index. The authors compare the results of these two methodologies. Findings. The Herfindahl-Hirschman Index (HHI) and the Lauraéus-Kaivo-oja Index are statistical measures of market concentration, and they can be used to determine market competitiveness. This paper demonstrates novel data analytics possibilities of new market data collected by the Statzon, Ltd with various comparative analytical results and findings. By our analyses we can help multiple industrial stakeholders make faster decisions and better strategic plans with the easiest and fastest access to accurate, reliable, and up-to-date cobotics industry statistics, forecasts, and insights. The finding is that this study reveals the current market structure of global cobotics. It is a novel finding and result. Originality / Value / Practical implications. This paper demonstrates the novel and exciting possibilities of transparent index calculation tools. The authors provide original results. Authors underline that extra value added to stakeholders and customers will be provided by joint data pooling strategy of various data sources, which is a key approach of this paper. Real-time market structure analyses create reliable and knowledge-based information for decision-makers and stakeholders of the global cobotics industry.

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Section: Resultsmentioning

confidence: 99%

Market Structure analysis with Herfindahl-Hirchman Index and Lauraéus-Kaivo-Oja Indices in the Global Cobotics Markets

Lauraéus

Kaivo‐oja

Knudsen

et al. 2021

Economics and Culture

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“…Following the procedure detailed in the UNI EN ISO 9283 standard regulation [10], the robot has been positioned in = 5 different locations of its workspace, and, for each cycle, the robot moved to the five positions , for a total of = 30 times. Five AMs of size 50 × 30 × 20 mm 3 have been positioned on a table following the shape described in Reference [10] and shown in Figure 5. To perform the measurements, the same single-axis proximity sensor used for the experiment in Section 4.2 has been mounted on the robot end-effector.…”

Section: Positioning Repeatability Performances After Three-points Anmentioning

confidence: 99%

“…Since their first introduction in 1996 [1,2], collaborative robots (cobots) have gained more and more relevance for manufacturing industries as a key technology to improve the production line, in compliance with the Industry 4.0 paradigm [3]. They are today adopted in the new collaborative workstations and in the hybrid meta-collaborative workstations [4], where humans and robots collaborate, thanks to the establishment of a common communication method.…”

Section: Introductionmentioning

confidence: 99%

Cobot User Frame Calibration: Evaluation and Comparison between Positioning Repeatability Performances Achieved by Traditional and Vision-Based Methods

et al. 2021

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Since cobots are designed to be flexible, they are frequently repositioned to change the production line according to the needs; hence, their working area (user frame) needs to be often calibrated. Therefore, it is important to adopt a fast and intuitive user frame calibration method that allows even non-expert users to perform the procedure effectively, reducing the possible mistakes that may arise in such contexts. The aim of this work was to quantitatively assess the performance of different user frame calibration procedures in terms of accuracy, complexity, and calibration time, to allow a reliable choice of which calibration method to adopt and the number of calibration points to use, given the requirements of the specific application. This has been done by first analyzing the performances of a Rethink Robotics Sawyer robot built-in user frame calibration method (Robot Positioning System, RPS) based on the analysis of a fiducial marker distortion obtained from the image acquired by the wrist camera. This resulted in a quantitative analysis of the limitations of this approach that only computes local calibration planes, highlighting the reduction of performances observed. Hence, the analysis focused on the comparison between two traditional calibration methods involving rigid markers to determine the best number of calibration points to adopt to achieve good repeatability performances. The analysis shows that, among the three methods, the RPS one resulted in very poor repeatability performances (1.42 mm), while the three and five points calibration methods achieve lower values (0.33 mm and 0.12 mm, respectively) which are closer to the reference repeatability (0.08 mm). Moreover, comparing the overall calibration times achieved by the three methods, it is shown that, incrementing the number of calibration points to more than five, it is not suggested since it could lead to a plateau in the performances, while increasing the overall calibration time.

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“…Human robot collaboration is a central component in Industry 4.0 [1], which necessitates robots' operation outside their restrained areas, in close distance to humans [2]. Efficient and effective human-robot cooperation, i.e.…”

Section: Introductionmentioning

confidence: 99%

Intuitive and Safe Interaction in Multi-User Human Robot Collaboration Environments through Augmented Reality Displays

Tsamis

Chantziaras

Giakoumis

et al. 2021

2021 30th IEEE International Conference on Robot &Amp; Human Interactive Communication (RO-MAN)

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As autonomous collaborative robots are more widely used in work environments alongside humans it is of great importance to facilitate the communication between people and robotic systems, in a way that promotes safety and productivity. To this end, we propose an Augmented Reality (AR) based system that allows workers in a human-robot collaborative environment to interact with a robot while also receiving information regarding the robot state and plans that relate to the human's safety and trust, such as the intended movement of the robotic arm or the navigation plan of the mobile platform. To evaluate the effectiveness of the proposed system we conducted experiments with 13 participants, where two users had to work in the same workspace while being assisted by a mobile manipulator. We measured the task completion time as well as the robot idle time using our ARbased human-robot interaction system and compared them to a conventional setup without the use of augmented reality. Additional, subjective evaluations related to user satisfaction, system usability, perceived safety and trust showed that users assessed the system in a positive way and preferred AR visualization over more traditional interfaces.

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Collaborative Robots and Industrial Revolution 4.0 (IR 4.0)

Cited by 146 publications

References 11 publications

Market Structure analysis with Herfindahl-Hirchman Index and Lauraéus-Kaivo-Oja Indices in the Global Cobotics Markets

Market Structure analysis with Herfindahl-Hirchman Index and Lauraéus-Kaivo-Oja Indices in the Global Cobotics Markets

Cobot User Frame Calibration: Evaluation and Comparison between Positioning Repeatability Performances Achieved by Traditional and Vision-Based Methods

Intuitive and Safe Interaction in Multi-User Human Robot Collaboration Environments through Augmented Reality Displays

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