Zhaoxin Zhu

Papers

Total Citations

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About

Zhaoxin Zhu is a researcher specializing in computer vision and robotic manipulation, with a particular focus on object grasping in challenging visual environments. His most-cited work, "An object planar grasping pose detection algorithm in low-light scenes" (2024), addresses a critical gap in robotic perception by developing robust methods for identifying and planning grasps under poor illumination—a common yet underexplored condition in real-world automation. This contribution has already garnered 3 citations, signaling early impact in the field. Zhu’s research bridges the gap between theoretical computer vision algorithms and practical robotic applications, aiming to enhance the reliability of autonomous systems in warehouses, manufacturing, and service robotics. By tackling low-light scenarios, his work directly improves the safety and efficiency of robots operating in dimly lit environments, such as nighttime logistics or underground facilities. As an emerging voice in robotic grasping, Zhu’s focus on real-world constraints positions him as a promising contributor to the next generation of adaptive, vision-driven robotic systems.