Hongzhang Zheng

Papers

Total Citations

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About

Hongzhang Zheng is a researcher at the forefront of intelligent robotics and autonomous systems, with a primary focus on navigation, obstacle avoidance, and industrial inspection. His most notable contribution is the development of a hybrid navigation algorithm that integrates A* path planning with the Timed Elastic Band (TEB) approach, enabling robust and efficient autonomous navigation in complex, obstacle-rich environments. This work, published in 2023, has already garnered 11 citations, reflecting its immediate relevance to the growing fields of driverless vehicles, service robotics, and safety inspection systems. Zheng’s research addresses critical real-world challenges, from sweeping robots to autonomous cars. In a separate line of inquiry, he applied deep learning—specifically Faster R-CNN—to automate the detection and hardness classification of aircraft bolts, a task traditionally performed manually. This work, though earlier and with 2 citations, underscores his versatility in applying AI to industrial quality control. Together, Zheng’s contributions demonstrate a clear trajectory toward safer, smarter, and more autonomous systems, making his research highly valuable for students and engineers working in robotics, computer vision, and intelligent manufacturing.