Ben Wang

California University of Pennsylvania, Nanjing University of Posts and Telecommunications, Hangzhou Normal University

Papers

Total Citations

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About

Ben Wang is a multidisciplinary robotics and computer vision researcher whose work spans visual perception, control systems, and humanoid robotics. His most recognized contribution, "LFTag: A Scalable Visual Fiducial System with Low Spatial Frequency" (2020, 7 citations), addresses a fundamental challenge in robotics and augmented reality by introducing a novel fiducial marker system that leverages topological detection and relative position encoding to achieve superior data density and robustness for 6-DOF monocular pose estimation. Complementing this, his work on adaptive non-singular terminal sliding mode control for robotic manipulators (2019, 3 citations) demonstrates his strength in advancing reliable, disturbance-resilient control strategies for physical robotic systems. More recently, Wang has extended his focus toward cutting-edge challenges, contributing to the growing discourse on humanoid robotics through a forward-looking survey of progress and future research directions (2025). His 2024 work on lightweight super-resolution for Chinese scene text reflects an expanding interest in perception enhancement for autonomous systems. Collectively, Wang's research positions him as a versatile contributor bridging low-level control, visual sensing, and intelligent perception — areas central to the next generation of autonomous and humanoid robotic platforms.