In past decades, robotics and neural network technology has been extensively studied in control engineering, aerospace, automotive, energy science, and many other fields. In order to increase the degree of automation and efficiency, the industries will increasingly utilize IoT, robotics, AI and others. The use of highly adaptable robotic systems will expand the range of tasks that can be automated and will also help speed up the production, future robotics will be more proficient in handling various tasks in the industry and society. With the emergence of the Industry 4.0, artificial intelligence (AI) and advanced manufacturing have become the backbone of the promotion of industrial upgrading and the transformation of the real economy, every industry requires some automation and intelligence that is combined in the form of embedded systems. How to combine intelligent methods to promote the rapid development of advanced manufacturing and achieve sustainable development has become a challenge facing more and more professionals.
Nowadays, the Internet and Cyber-Physical System (CPS) constitute an important part of daily life. CPS is the integration of physical and logical systems, including the interaction between digital, analog and artificial components. These systems are the establishment factors for various applications. The next generation of industry will be built on CPS. With the development and popularization of CPS technology, the use of computers and networks to achieve functional expansion of physical equipment is ubiquitous, and will promote the upgrading of industrial products and technologies, greatly improving the competitiveness in major industrial fields such as aerospace, defense, industrial automation, etc.
This research topic is devoted to exploring the key theories, latest trends and application prospects in the field of robotics, neural networks and CPS in tackling the challenges pose for sustainable development and advanced manufacturing. To achieve this goal, this research topic will seek the latest research in the following areas, including but not limited to:
• Artificial neural computation
• Biological neural network modeling
• Robotics and intelligent information system
• Sensors and data processing in robotics
• CPS safety and security
• Neural network learning methods
• Robotics within advanced manufacturing
• CPS with federated learning (FL) and AI techniques
• Embedded AI and machine learning for real-time CPS
• Biometric systems and forensics applications
• Key supporting technologies for robotics, neural networks and CPS
All contributions should be within the scope of this Research Topic and the journal.
In past decades, robotics and neural network technology has been extensively studied in control engineering, aerospace, automotive, energy science, and many other fields. In order to increase the degree of automation and efficiency, the industries will increasingly utilize IoT, robotics, AI and others. The use of highly adaptable robotic systems will expand the range of tasks that can be automated and will also help speed up the production, future robotics will be more proficient in handling various tasks in the industry and society. With the emergence of the Industry 4.0, artificial intelligence (AI) and advanced manufacturing have become the backbone of the promotion of industrial upgrading and the transformation of the real economy, every industry requires some automation and intelligence that is combined in the form of embedded systems. How to combine intelligent methods to promote the rapid development of advanced manufacturing and achieve sustainable development has become a challenge facing more and more professionals.
Nowadays, the Internet and Cyber-Physical System (CPS) constitute an important part of daily life. CPS is the integration of physical and logical systems, including the interaction between digital, analog and artificial components. These systems are the establishment factors for various applications. The next generation of industry will be built on CPS. With the development and popularization of CPS technology, the use of computers and networks to achieve functional expansion of physical equipment is ubiquitous, and will promote the upgrading of industrial products and technologies, greatly improving the competitiveness in major industrial fields such as aerospace, defense, industrial automation, etc.
This research topic is devoted to exploring the key theories, latest trends and application prospects in the field of robotics, neural networks and CPS in tackling the challenges pose for sustainable development and advanced manufacturing. To achieve this goal, this research topic will seek the latest research in the following areas, including but not limited to:
• Artificial neural computation
• Biological neural network modeling
• Robotics and intelligent information system
• Sensors and data processing in robotics
• CPS safety and security
• Neural network learning methods
• Robotics within advanced manufacturing
• CPS with federated learning (FL) and AI techniques
• Embedded AI and machine learning for real-time CPS
• Biometric systems and forensics applications
• Key supporting technologies for robotics, neural networks and CPS
All contributions should be within the scope of this Research Topic and the journal.
