Chengshun Yu

Beijing University of Posts and Telecommunications

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About

Chengshun Yu is a leading researcher at the intersection of robotics, tactile perception, and intelligent manipulation. His work centers on advancing robotic grasping by integrating visual and tactile feedback, particularly for multi-fingered hands—a critical step toward more dexterous and adaptive automation. Yu’s most influential contribution, “A comprehensive review of robot intelligent grasping based on tactile perception” (2024, 67 citations), provides a foundational synthesis of the field, mapping how tactile sensing enhances grasp planning and control. He also introduced the VTG dataset (2024, 6 citations), a pioneering visual-tactile resource specifically designed for three-fingered grasp configurations. This dataset addresses a key gap in the literature, as prior work largely focused on simpler grippers, whereas three-fingered hands offer richer contact points and finer manipulation capabilities. By enabling more complex grasping modes for diverse object shapes, Yu’s research directly supports progress in industrial automation, assistive robotics, and human-robot interaction. His work is already shaping how robots perceive and interact with the physical world, making him a rising voice in embodied AI and sensor-driven robotics.