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About

Peihan Huang is a rising innovator at the intersection of self-powered sensing, robotics, and environmental intelligence. Their research focuses on developing multi-modal perception systems that integrate triboelectric nanogenerators (TENGs) and micro thermoelectric generators (MTEGs) to enable reliable, energy-autonomous sensing in challenging environments. Huang’s major contributions include pioneering a dual-modal material identification method that synergizes MTEG-TENG sensing with machine learning optimization, achieving robust accuracy across diverse conditions—a critical advancement for robotic tactile intelligence. Their work on underwater multi-dimensional tactile and flow velocity perception, as well as a novel sensing method for underwater robotic arm grasping, demonstrates a clear impact: these papers, published in 2025, have already garnered 3 and 2 citations each, signaling rapid recognition in the field. Notably, Huang’s approach addresses the fundamental challenge of sensor accuracy under environmental complexity, directly advancing the capabilities of autonomous underwater robots. This research not only pushes the boundaries of self-powered sensor systems but also lays the groundwork for next-generation intelligent robotics in harsh, real-world settings.