Sensor-Based Target Positioning Technologies in Industrial Automation

This thesis examines the critical role of sensor-based target positioning technologies in industrial automation within the context of Industry 4.0, highlighting their importance for operational efficiency and adaptability. Emphasizing the significance of sensors in automation, the study explores the principles, capabilities, and constraints of RFID, LiDAR, and WSN technologies, each pivotal for accurate target localization. It presents a comparative analysis of these technologies, focusing on their applications across various industrial scenarios, such as production lines, warehousing, and logistics, and evaluates their effectiveness through a series of experiments. The experimental analysis reveals RFID's precision improvement within 10 centimeters and LiDAR's enhanced accuracy with light information integration. It also shows that WSN's precision is contingent on noise levels, with the distance-corrected iterative localization algorithm significantly reducing localization error. The study concludes that while advancements have been made, future research should address the limitations observed in harsh industrial environments, with an emphasis on machine learning and AI integration for data processing to navigate environmental challenges.