Industrial robots are a strategic future technology and an important part of the development of artificial intelligence, and they are a necessary means for the intelligent transformation of manufacturing industry. Based on global industrial robot trade data from 1998 to 2017, this paper applies the dynamic complex network analysis method to reveal the spatial and temporal variation characteristics and trade status evolution of the global industrial robot trade network. The results show that the global industrial robot network density has steadily increased, and the industrial robot trade has been characterized by 'diversification'. The number of major industrial robot exporters in the world is increasing, and the import market is increasingly diversified. The export market structure is relatively tight, the centrality of the global industrial robot trade network shows a downward trend, and the dissimilarity of the 'core-edge' clusters decreases year by year. The trade status of 'catch-up' countries represented by China has rapidly increased. However, Japan, Germany, and Italy are still in the central position of the industrial robot trade. Moreover, trade of the 'catch-up' countries' is dominated by imports, and exports of industrial robot products are insufficient. Finally, policy suggestions are provided according to the results.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6762107 | PMC |
| http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0222785 | PLOS |
Publication Analysis
Top Keywords
Similar Publications
A Bibliometric Review of Brain-Computer Interfaces in Motor Imagery and Steady-State Visually Evoked Potentials for Applications in Rehabilitation and Robotics.
Sensors (Basel)
December 2024
Instituto de Automática e Informática Industrial, Universitat Politècnica de València, 46022 Valencia, Spain.
In this paper, a bibliometric review is conducted on brain-computer interfaces (BCI) in non-invasive paradigms like motor imagery (MI) and steady-state visually evoked potentials (SSVEP) for applications in rehabilitation and robotics. An exploratory and descriptive approach is used in the analysis. Computational tools such as the biblioshiny application for R-Bibliometrix and VOSViewer are employed to generate data on years, sources, authors, affiliation, country, documents, co-author, co-citation, and co-occurrence.
View Article and Find Full Text PDFStudy of Positioning Accuracy Parameters in Selected Configurations of a Modular Industrial Robot-Part 1.
Sensors (Basel)
December 2024
Institute of Mechanical Technology, Poznan University of Technology, 60-965 Poznan, Poland.
This article presents the fundamental principles of robot accuracy. It characterizes a modular robot, describes the measurement setup, and outlines the methodology for evaluating positioning accuracy across different configurations of the modular robot (four, five, and six modules) under varying loads of 6, 10, and 16 kg. An analysis was conducted on the impact of load changes on four- and five-module configurations, as well as the effect of configuration changes on the robot's performance with 6 and 10 kg loads.
View Article and Find Full Text PDFPredictive Maintenance and Fault Detection for Motor Drive Control Systems in Industrial Robots Using CNN-RNN-Based Observers.
Sensors (Basel)
December 2024
Department of Computer Science and Engineering, Intelligent Robot Research Institute, Sun Moon University, Asan 31460, Republic of Korea.
This research work presents an integrated method leveraging Convolutional Neural Networks and Recurrent Neural Networks (CNN-RNN) to enhance the accuracy of predictive maintenance and fault detection in DC motor drives of industrial robots. We propose a new hybrid deep learning framework that combines CNNs with RNNs to improve the accuracy of fault prediction that may occur on a DC motor drive during task processing. The CNN-RNN model determines the optimal maintenance strategy based on data collected from sensors, such as air temperature, process temperature, rotational speed, and so forth.
View Article and Find Full Text PDFTemperature Uniformity Control of 12-Inch Semiconductor Wafer Chuck Using Double-Wall TPMS in Additive Manufacturing.
Materials (Basel)
January 2025
Daegyung Technology Application Division, Korea Institute of Industrial Technology, Daegu-si 42994, Republic of Korea.
In semiconductor inspection equipment, a chuck used to hold a wafer is equipped with a cooling or heating system for temperature uniformity across the surface of the wafer. Surface temperature uniformity is important for increasing semiconductor inspection speed. Triply periodic minimal surfaces (TPMSs) are proposed to enhance temperature uniformity.
View Article and Find Full Text PDFHuman-Inspired Control of a Whip: Preparatory Movements Improve Hitting a Target.
Proc IEEE RAS EMBS Int Conf Biomed Robot Biomechatron
September 2024
Department of Biology, Northeastern University, Boston, MA, USA.
Manipulating flexible and underactuated objects, such as a whip, remains a significant challenge in robotics. Remarkably, humans can skillfully manipulate such objects to achieve tasks, ranging from hitting distant targets to extinguishing a cigarette's in someone's mouth with the tip of a whip. This study explored this problem by constructing and modeling a 25-degree-of-freedom whip.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!