Near Infrared Light-Based Non-Contact Sensing System for Robotics Applications

Abstract

With the development of artificial intelligence and the Internet of Things, non-contact sensors are expected to realize complex human-computer interaction. However, current non-contact sensors are mainly limited by accuracy and stability. Herein, an intelligent infrared photothermal non-contact sensing system is developed that provides long-distance and high-accuracy non-contact sensing. A black phosphorus (BP)-based composite organogel is designed, which exhibits excellent photothermal properties and environmental stability, as the active material. This material can detect patterns created by near-infrared (NIR) light through various patterned masks monitored by an infrared thermal imager. The constructed non-contact sensing system is capable of accurately recognizing 26 letters with an impressive accuracy rate of 99.4%. Furthermore, even small size non-contact sensors can maintain high sensitivity and stability across a wide temperature range, at long working distances, and under different current intensities and dark conditions, demonstrating exceptional robustness. Combined with machine learning method, it is demonstrated that the non-contact sensing system excels in pattern recognition and human-computer interaction. These features highlight its potential applications in intelligent robotics and remote control systems.