Recently, the Ultrafast Photonics Team at the School of Optoelectronic Engineering, Xidian University, has made a significant breakthrough in the field of on-chip intelligent LiDAR. The team has innovatively combined optical phased arrays with polarization-resolved photonic neural networks, enabling LiDAR to not only acquire three-dimensional positional information of targets but also utilize polarization information in echoes to identify target materials. This achievement provides a novel approach to enhancing the environmental perception capabilities of unmanned systems. The related research, titled "Optical phased array LiDAR chips towards polarization-resolved 4D sensing," was published in the internationally renowned academic journal Nature Communications in September 2026. By constructing a chip-scale photonic system that combines scanning ranging and material property discrimination capabilities, the research team has achieved "four-dimensional sensing" by adding point-by-point material attributes to the three-dimensional spatial coordinates. Experimental results demonstrate that the system achieves over 85% classification accuracy for three types of materials—wood, stone, and steel—within a 10-meter range, with single-point ranging accuracy reaching ±0.1 meters. This breakthrough provides crucial technical support for applications such as intelligent robots, environmental perception in unmanned platforms, and industrial target detection.