Abstract: The deployment of pose detection and control technology in heading equipment are critical elements to im⁃ prove intelligence application in coal mining process，which would further reduce coal mining accident rate effectively. Both visual pose detection and control technology require information perception and status check implementation in practical application，which could be achieved by visual measurement technology，a popular research topic in recent years.When factoring visual pose detection and control features in heading equipment application，some key techniques include but not limited to image acquisition， image preprocessing， feature extraction， pose calculation， pose measurement error analysis，compensation technology，visual servo control，directional navigation technology and shape cutting control technology.Specifically，taking boom⁃type roadheader as an example，the application of visual pose detection is studied， which mainly include boom⁃type roadheader body pose detection and cutting head of boom⁃type roadheader pose detection.The study analyzes discrepancies and deficiencies issues within the existing visual pose detection methods and potential problems in the development of directional navigation control technology and the automatic shape cutting control technology.The study specifically points out that high dust，low intensity of illu⁃ mination，strong vibration，and serious electromagnetic interference environment are the triggering points causing tech⁃ nical problems on the pose detection and control of heading equipment in coal heading process.These triggering points would further cause low detection accuracy rate，unstable feature extraction results，diversity in visual detection，ineffi⁃ ciency in target installation with terrain changing unadjusted，and insufficiency in remote measurement and control in⁃ telligence application.Lastly，regarding these difficult technical problems of visual pose detection and control，the study provides some breakthrough ideas including optimizing vision detection scheme，improving feature extraction algorithm， upgrading image acquisition hardware，and bringing insights on improving pose detection technology under complex ter⁃ rain and digital twin drive remote monitoring technology.With the improvement of accuracy，real⁃time，stability，and ro⁃ bustness of the visual detection system to obtain better coal mine information，the intelligent perception is realized and the intelligent degree of coal mine is improved.