Zhenghan Jiang

Papers

Total Citations

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About

Zhenghan Jiang is a robotics researcher whose work focuses on autonomous navigation and perception, particularly in challenging environmental conditions. His most cited paper, "Depth Image-Based Obstacle Avoidance for an In-Door Patrol Robot" (2019, 9 citations), addresses a critical limitation in traditional vision-based systems: their reliance on adequate lighting. By leveraging depth imaging, Jiang demonstrated that robots can reliably detect and avoid obstacles even in complete darkness, a significant advancement for indoor patrol and security applications. This contribution bridges the gap between conventional RGB-based methods and practical deployment in low-light scenarios, enhancing the robustness of autonomous mobile robots. Jiang’s research underscores the importance of sensor fusion and depth perception in real-world robotics, offering a scalable solution for safer, more reliable autonomous navigation. His work continues to influence the development of resilient robotic systems, making him a notable figure in the field of intelligent robotics and computer vision.