Abstract: The research focused on addressing various challenges in intelligent top caving theory, intelligent perception and recognition key technology, intelligent caving comprehensive decision-making technology, and remote caving intelligent control technology of fully mechanized top coal caving face. This is being done under the “13th Five-Year” national key research and development plan, specifically designed for the key technology and demonstration of intelligent fully mechanized top coal caving mining method with annual production of 10 million of tons in extra-thick coal seam. The research has resulted in the following outcomes: ① Comprehensive experiments were conducted to understand the interaction process of crushing and migrating of roof and top coal combination (RTCC) and the fragmentation distribution of RTCC under different roof conditions. A three-dimensional laser goaf space detection technology has been developed, and the arching phenomenon of top coal blocks on contact, at coal discharge process with multiple coal discharge ports, has been validated. In addition, the numerical simulation of multi-port intelligent coal caving in extra-thick coal seam is carried out with the constraints of mining and caving coordination, high recovery rate, and low gangue ratio, and the number of coal caving ports is determined. those provide a reliable theoretical basis for optimizing intelligent coal-caving processes. ②The research has explored the geological information and physical characteristics of coal and gangue in the working face, along with full-cycle sensing elements of the top coal caving process. This has led to the development of a comprehensive sensing technology system, including real time detection of top coal thickness, accurate identification of coal and gangue, and dynamic measurement of coal flow, providing crucial data information support for decision making of intelligent coal top caving technology. ③A multi-source information database has been established for the man-machine-environment interface, and a decision-making model has been developed for fully mechanized top caving in extra-thick coal seams. An intelligent coal top caving decision-making software based on the Q-learning algorithm has been created, utilizing artificial intelligence for coal and gangue identification, top coal thickness detection, and coal quantity monitoring. ④A high-precision inertial navigation monitoring and control technology for intelligent fully mechanized caving faces has been developed, enabling real-time positioning, attitude monitoring, and action control for the shearer, hydraulic support, and scraper conveyor. An intelligent mine-integrated communication scheduling system and a remote-integrated control platform for fully mechanized caving have also been established. Those allow for the successful implementation of intelligent coal caving in remote one-button start mode. ⑤Advanced technologies such as ground-penetrating radar for top coal thickness detection, vibration-audio-hyperspectral for coal-gangue identification, and laser three-dimensional scanning for real-time coal caving monitoring are utilized in the 8222 Working Face of Tashan Mine. Intelligent coal caving decision software is applied in fully mechanized caving operations, leading to a control of errors within 10.71% for top coal thickness detection, 9.32% for mixed gangue rate, and 7.8% for coal caving amount. On average, each coal caving cycle now saves about 30 minutes, leading to intelligent and efficient coal caving operations with an annual output of 15 million tons.