为解决当前煤矿巷道综掘工作面的智能化程度较低，掘进效率低下的问题，分析了煤矿综掘工作面实现智能化快速掘进的关键是自主感知和调控技术。

 首先，探讨了智能化掘进的关键技术特征，煤矿综合掘进机器人化装备以智能感知技术、自主控制决策技术、群组协同作业技术为支撑，形成智能化快速掘进技术体系构架，实现探-掘-护-锚一体化协同作业。 

其次，重点阐述了智能化掘进的自主感知技术包括基于超宽带原理的位姿感知、基于双频激电法的超前探测、基于 SLAM 原理的环境感知、基于变迁记忆故障 Petri 网的故障感知等，自主调控技术包括基于群体智能算法的智能截割、基于遗传变异粒子群算法的路径规划、基于 BP 神经网络 PID 算法的自主纠偏等。

 再次，详细论述了智能临时支护感知包括围岩压力、顶底板状况、支架位姿等多维信息的感知，研究了非水平场景下掘支协同与多机组多缸联动的自适应控制方法;介绍了智能永久支护感知包括围岩位移感知和支护装备受力变形感知，并探讨了锚护网络结构优化方法，自适应钻进控制上为获得最佳推进力控制性能，提出基于粒子群优化算法的自抗扰控制器参数整定略。 

最后，探讨了煤矿巷道智能化掘进的自主感知及调控技术的进一步发展方向。

In order to solve the problems of low intelligentization and low driving efficiency of current coal mine com- prehensive heading face,the key to realizing intelligent rapid heading in coal mine comprehensive heading face is autonomous sensing and control technology. Firstly,the key technical features of intelligent heading are discussed. The robotic equipment for coal mine comprehensive heading is supported by intelligent perception technology,auton- omous control decision-making technology,and group collaborative operation technology to form an intelligent rapid heading technology system framework to achieve exploration-heading-support-anchor inte-gration cooperation. Sec- ondly,it focuses on the self-aware technology of intelligent excavation, including posture perception based on the principle of ultra-wideband,advanced detection based on the dual-frequency electric shock method,environmental perception based on the principle of SLAM,and fault perception based on the transition memory fault Petri net,etc. Autonomous control technology includes intelligent cutting based on swarm intelligence algorithm, path planning based on genetic mutation particle swarm optimization algorithm,autonomous correction based on PID algorithm of BP neural network and so on. Thirdly,it discusses in detail the perception of intelligent temporary support including multi-dimensional information such as surrounding rock pressure,roof and floor conditions,support posture,etc. ,and studies the adaptive control method for the linkage of excavation support and multi-unit multi-cylinder under non- horizontal scenarios. Intelligent permanent support perception includes surrounding rock displacement perception and support equipment stress deformation perception,and discusses the optimization method of anchor network structure. In order to obtain the best propulsion control performance in adaptive drilling control,a particle swarm optimization parameter tuning strategy of the algorithm’ s auto disturbance rejection controller is proposed. Finally,the direction of further development of autonomous perception and control technology for intelligent tunneling of coal mine roadways is discussed.