A paradigm shift from traditional non-contact sensors to tele-perception

Abstract

With the rapid advancement of embodied perception technologies, the demand for enhanced interaction versatility, extended perceptual reach, and heightened sensitivity in human-machine interfaces (HMI) continues to grow. Triboelectric nanogenerator (TENG) based non-contact sensors have emerged as a transformative solution, offering exceptional adaptability while mitigating challenges such as mechanical degradation and potential health risks. However, achieving superior sensitivity and extending sensing ranges remain critical bottlenecks. Addressing these limitations, researchers have pioneered the concept of tele-perception, a groundbreaking innovation that breaks the limitations of traditional non-contact sensors by enabling precise, long-range perceptual capabilities. This review explores the paradigm shift from traditional non-contact sensors to tele-perception, highlighting the foundational principles, representative system architectures, and cutting-edge optimization strategies that define this new approach to sensing without physical interaction. Particular emphasis is placed on the integration of advanced charge-trapping mechanisms to enhance electrostatic charge stability and the deployment of intelligent algorithms and deep learning (DL) techniques to advance tele-perception functionalities. Concluding with an analysis of the challenges and future opportunities in tele-perception systems development, this review offers critical insights to guide next-generation research and applications in this transformative field.