The Application and Improvement of Industrial Robot and Neural Network

The field of industrial robotics and neural networks is central to the ongoing transformation of modern industry. Robotics provides efficient solutions for physical automation, incorporating mechanical design, advanced sensors, and precise control systems, while neural networks—an influential subset of artificial intelligence—impart adaptability and decision-making capabilities through pattern recognition and deep learning techniques. The synergy between these domains has enabled robots to shift from simple, repetitive executors to collaborative partners capable of handling complex tasks. Recent breakthroughs in computer vision, deep neural architectures, and sensor fusion have greatly contributed to the expanding role of smart robots across manufacturing, logistics, and inspection. However, significant questions remain about how to effectively deploy data-efficient AI models on industrial robots, ensure robust real-time operation in dynamic environments, and harmoniously integrate advanced algorithms with practical hardware constraints.This Research Topic aims to address the next generation of challenges and opportunities in merging industrial robotics with neural network-based intelligence. The goal is to foster cutting-edge research that advances the understanding and application of lightweight, high-performance AI models for industrial robots. Key objectives include exploring innovative approaches to training neural networks with limited datasets, optimizing robotic workflows for greater productivity and reliability, and pioneering new application scenarios that demonstrate the tangible benefits of this integration in real-world industries. Through these aims, the research will contribute to safer, smarter, and more adaptable industrial systems that significantly impact efficiency and workforce collaboration.This Research Topic welcomes research that bridges theory and practical implementation but remains focused on the intersection of industrial robots and neural networks. It encourages submissions that propose novel techniques, evaluate real-world deployment, or synthesize current progress in this interdisciplinary field. To gather further insights into these transformative technologies, we invite articles addressing, but not limited to, the following themes:• Applications of artificial intelligence and neural networks in industrial settings• Advances in the deployment and improvement of industrial robots• Optimization and practical integration of AI algorithms in robotics• Training and implementing lightweight neural networks using limited data• Enhancing industrial robot efficiency with intelligent algorithms• Emerging unmanned inspection technologies, including underwater and remote environments• Techniques in prognostics and health management for robotic systems• Hybrid approaches in physical modeling and knowledge-driven integrated learningWe welcome original research articles, comprehensive review papers, methodological contributions, and insightful case studies related to these themes. Topic editors: Zhen Yu, Lei Kou, Qi An, Abdelbadia Chaker Source: https://www.frontiersin.org/research-topics/81163/the-application-and-improvement-of-industrial-robot-and-neural-network