Robotic Vision System: Recent Development Trends and Challenges

Robotic vision systems have become integral to modern industrial automation, enabling high-precision manufacturing, real-time quality inspection, and autonomous decision-making. This study explores the latest advancements, key challenges, and future prospects of robotic vision in industrial applications. It examines issues related to real-time target recognition, algorithm optimization, system stability, and integration with intelligent control systems. Additionally, emerging technologies such as deep learning-based vision enhancement, multi-sensor fusion, and Vision-Based Tactile Sensors (VBTS) are analyzed for their potential to improve adaptability and efficiency. The findings highlight both the limitations and the promising trajectory of robotic vision systems, emphasizing the need for continued research in real-time processing, hardware optimization, and AI-driven decision-making. By addressing these critical aspects, this study provides valuable insights for researchers and industry professionals seeking to enhance the performance and reliability of robotic vision technologies.