Haitian Xie

University of Electronic Science and Technology of China

Papers

Total Citations

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About

Haitian Xie is a leading researcher in intelligent robotics, with a primary focus on autonomous inspection systems and advanced navigation for substation environments. His most influential work, "A robust pointer meter reading recognition method for substation inspection robot" (2017, 38 citations), revolutionized automated visual inspection by introducing a two-stage algorithm that leverages template-based scale line centroid detection and least-square fitting. This method enables robots to accurately read analog meters under challenging real-world conditions, directly enhancing the reliability of unmanned substation operations. Xie further advanced robotic autonomy through his work on "An Improved Obstacle Avoidance Method for Robot Based on Constraint of Obstacle Boundary Condition" (2017, 4 citations), where he integrated odometer, IMU, and laser radar data to develop a novel algorithm that uses obstacle boundary constraints for safer, more efficient path planning. By fusing multi-sensor data with boundary-aware navigation, Xie has contributed foundational techniques that bridge perception and motion control in cluttered industrial settings. His research continues to influence the design of robust, field-deployable inspection robots, making him a key figure in the evolution of intelligent substation automation.