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About

Xiuchen Jiang is a leading researcher in intelligent robotics and computer vision for power infrastructure, with a focus on advancing the automation and cognitive capabilities of substation inspection systems. His work centers on three key areas: multimodal image processing, robotic pose relocalization, and object recognition for power equipment. Jiang’s major contributions include developing a quadrilateral-feature-based method for registering visible and infrared images—critical for combining thermal and visual diagnostics—and pioneering an active pose relocalization technique that enables inspection robots to consistently capture images aligned with calibration standards, achieving 25 citations. He also advanced cognitive intelligence in robotics by introducing human-level concept learning for power equipment defect detection, moving beyond simple perceptual tasks. His recent BIM-based 3-D multimodal reconstruction approach (2024) further reduces human workload by transforming 2-D inspection images into three-dimensional models. With over 50 total citations and a growing impact, Jiang’s work is foundational to the next generation of autonomous, intelligent inspection systems, directly improving the reliability and safety of electrical grid operations.