Abstract: Coal rock recognition technology can provide a basis for automatization improvement of shearer and is the key to achieving intelligent unmanned mining in coal mines. The existing coal rock recognition technologies include image recognition, process signal monitoring recognition, electromagnetic wave recognition, and ultrasonic detection recognition, multi-sensor fusion recognition. This article provides a detailed introduction to the principles and application status of the above-mentioned technologies. ① Image recognition technology is currently in the experimental stage, mainly involving large-scale coal rock image data annotation and recognition problems under complex geological conditions. ② Process signal monitoring and recognition technology can analyze relevant signals during coal mining and recognize potential coal rock interface information. But it needs to solve the problems of signal noise interference and complex coal rock interface recognition. ③ Electromagnetic wave recognition technology and ultrasonic detection recognition technology have been applied in actual coal rock interface detection. But there is still a need to improve recognition accuracy and reliability, especially for complex coal rock structures and interface situations. ④ Multi sensor fusion recognition technology needs to solve the problem of data fusion and matching, ensure accurate calibration and reliability between different sensors, and verify its feasibility and practicality in practical applications. In order to solve the above problems, the development directions of coal rock recognition technology are pointed out. ① Research on coal rock recognition should focus on improving the real-time performance and anti-interference capability of algorithms. It will ensure accurate recognition of coal rock under specific conditions and complex environmental interference, and meet the actual mining needs underground. ② Research on coal rock recognition should strengthen the research on mining sensors to improve their anti-interference performance. It is suggested to adopt advanced visual cameras and intelligent devices to combine with sensors to improve the precision and efficiency of coal rock recognition. ③ Research on coal rock recognition should focus on the cross fusion of multiple coal and rock recognition technologies. For coal and rock with different hardness, process signal monitoring recognition and multi-sensor fusion technology can be adopted. For cases with similar hardness, image recognition and electromagnetic wave recognition techniques can be combined to achieve accurate recognition of coal rock wall interfaces and coal seam thickness.