Near Infrared Light‐Based Non‐Contact Sensing System for Robotics Applications
Ran Wang, Yu Cheng, Qiran Zhang, Haoran Li, Yangyang Wang, Jiaqi Liu, Ruirui Xing, Jinming Ma, Tifeng Jiao
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.