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A complex stratum formed due to the influence of internal and external dynamic geological processes will lead to extremely complex mining conditions in deep exploration and development of oil, gas, coal and other resources, processes mainly threatened by disasters such as coal and gas conflict, mine water inrush, and rock burst. Combined with formation identification and measurement while drilling technology, the drilling level of underground drilling robot in coal mines is constantly developing. In order to prevent coal mine accidents and achieve safe and efficient mining, efficient and accurate drilling is the key, and should be based on research on the influence of complex stratum on the drilling trajectory. In order to comprehensively and systematically summarize the research on the influence of a complex stratum on drilling tool mechanics, this paper describes the history and current situation of complex stratum exploration, measurement while drilling technology, borehole bending conditions, stress analysis of complex coal seams on drilling tools, formation force theory and method, and geosteering drilling technology. In addition, the research and application of directional drilling technology in gas control, water hazard prevention and geological anomaly detection are also discussed.

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The horizontal drilling trajectory of the anti-collision drilling robot is taken as the research object and its drilling trajectory prediction model is established in this paper. The drilling trajectory is affected by many factors, such as the structural parameters of the auger, the drill bit, the drilling process parameters, and the geological characteristics of the coal seam, etc., which results in the existence of multi-level time-scale structure and localization characteristics of the drilling trajectory data in the time domain. The wavelet analysis method can decompose the relatively complex non-stationary time series problem into low-frequency decomposition signals representing trend items and high-frequency decomposition signals representing periodicity and randomness. It can not only predict the main trend of drilling trajectory changes but also effectively predict sudden load changes and short-term changes. Based on this, a new prediction method is proposed in this paper. Firstly, the data is decomposed into relatively simple component signals using wavelet decomposition technology, then the prediction models are established according to the characteristics of each component signal. Finally, the drilling trajectory prediction model is established by synthesizing the prediction results. The anti-impact drilling robot drilling test bed is set up and the drilling experiments are carried out to verify the effectiveness of the model, which can lay the foundation for the anti-impact drilling robot drilling deflection control.