Zhuoheng Xiang

Changchun University of Science and Technology

Papers

Total Citations

H-Index

About

Zhuoheng Xiang is a researcher advancing the frontiers of intelligent robotics and automation, with a primary focus on visual simultaneous localization and mapping (SLAM) and precise indoor positioning. Their most notable contribution, "Accurate localization of indoor high similarity scenes using visual SLAM combined with loop closure detection algorithm" (2024), directly tackles a critical bottleneck in autonomous navigation: maintaining accuracy in visually ambiguous environments where traditional SLAM systems often fail. By integrating a robust loop closure detection algorithm, Xiang’s work enhances the reliability of robotic localization in complex, high-similarity indoor spaces—a key enabler for applications in warehouse logistics, service robotics, and automated manufacturing. Though early in their career, this work has already garnered attention, accumulating citations that underscore its relevance to the growing demand for robust autonomous systems. Xiang’s research bridges the gap between theoretical SLAM advances and practical deployment challenges, offering a solution that improves both mapping consistency and localization precision. As the field pushes toward fully autonomous indoor navigation, Xiang’s contributions represent a meaningful step in making intelligent robots more dependable in real-world, repetitive environments.