Zhuohan Li

Papers

Total Citations

H-Index

About

Zhuohan Li is a robotics researcher specializing in computer vision and autonomous manipulation, with a particular focus on RGB-D perception for robotic grasping. His most-cited work, "Target Position and Posture Recognition Based on RGB-D Images for Autonomous Grasping Robot Arm Manipulation" (2020, 7 citations), introduces a novel method that fuses RGB and depth images to enable precise target localization and orientation estimation. This contribution addresses a critical challenge in autonomous robotics—enabling robot arms to perceive and interact with objects in unstructured environments. By developing a robust recognition pipeline that combines visual and spatial data, Li's research directly advances the reliability of robotic grasping systems, a cornerstone for applications in manufacturing, logistics, and service robotics. Though early in his career, his work has already garnered attention for its practical approach to bridging perception and action. Li's contributions are particularly notable for their potential to improve human-robot collaboration, where accurate target recognition is essential for safe and efficient manipulation. His research continues to explore the integration of deep learning with traditional computer vision techniques, positioning him as an emerging voice in the field of autonomous robotic systems.