Yezhang Tu

Papers

Total Citations

H-Index

About

Yezhang Tu is a researcher specializing in mobile robotics and sensor fusion, with a particular focus on simultaneous localization and mapping (SLAM) in structured environments. His most cited work, "The Mobile Robot SLAM Based on Depth and Visual Sensing in Structured Environment" (2015), explores the integration of depth sensors and visual data to enhance robotic navigation and mapping accuracy. This contribution addresses critical challenges in autonomous systems, such as real-time environmental perception and robust localization, which are foundational for applications in industrial automation and service robotics. While his citation count remains modest, Tu’s research underscores the practical importance of combining multimodal sensing—like depth cameras and visual inputs—to improve SLAM performance in constrained settings. His work aligns with broader trends in robotics, where efficient sensor fusion is key to enabling reliable autonomy. For students and researchers entering the field, Tu’s study offers a clear example of how depth-visual integration can mitigate limitations of single-sensor approaches, making it a useful reference for those exploring low-cost, scalable robotic solutions.