Guoxing Wang

Shanghai Jiao Tong University, Beijing Satellite Navigation Center, Beijing Academy of Artificial Intelligence, Tongji University

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About

Guoxing Wang is a researcher at the forefront of bio-inspired robotics and intelligent perception systems, with a focus on enabling machines to interact with the physical world more naturally and adaptively. His work spans three key areas: tactile sensing for softness perception, efficient action recognition for human-computer interaction, and adaptive locomotion control for legged robots. Wang’s most notable contribution is the development of a self-adaptive perception framework that uses biomimetic mechanoreceptors to estimate an object’s deformability—a breakthrough that addresses a long-standing challenge in unstructured robotic manipulation. This work, published in 2023, has already garnered 18 citations for its novel integration of kinesthetic and cutaneous cues. In parallel, his AR-C3D architecture for real-time action recognition on FPGA hardware (2019, 11 citations) demonstrates a practical path toward low-latency human-computer interaction. Earlier research on central pattern generator (CPG)-based adaptive walking control for quadruped robots (2013, 11 citations) laid foundational insights for bio-inspired locomotion, while his stability analysis of cable-driven parallel robots (2023, 10 citations) advances optimal design in precision robotics. Wang’s interdisciplinary approach—combining neuroscience principles with engineering design—positions him as a rising innovator in creating robots that sense, move, and adapt like living organisms.