Zhang Chun

Papers

Total Citations

H-Index

About

Zhang Chun’s research lies at the intersection of tactile sensing, robotic perception, and 3D surface reconstruction, with a focus on advancing optical tactile sensors for dexterous manipulation. His most-cited work, “A 3-D Surface Reconstruction with Shadow Processing for Optical Tactile Sensors” (2018, 17 citations), introduces a novel technique that leverages a deformable sensing layer, an image sensor, and four individually controlled flashing LEDs to reconstruct three-dimensional surface geometries from shadow patterns. This contribution addresses a critical challenge in robotic touch: enabling fingers to perceive fine surface details through optical means. By integrating shadow processing into the reconstruction pipeline, Zhang’s method enhances the spatial resolution and robustness of tactile feedback, paving the way for more sensitive and adaptive robotic grippers. Though still early in his career, his work has already garnered attention in the tactile sensing community, with his 2018 paper serving as a foundational reference for researchers exploring vision-based tactile sensors. Zhang’s approach exemplifies how combining hardware innovation with computational geometry can unlock new capabilities in robotic perception, making his research a valuable resource for students and engineers working on next-generation haptic systems.