鉴于综掘工作面掘进机截割工作周期长、振动幅度大等工况环境约束，单一惯性导航系统由于导航误差随时间累积的影响，很难在综掘流程中实现自主、实时、精准感知掘进机的姿态和位置。以惯性导航系统为主系统，提出一种基于惯导系统与激光感知系统的掘进组合定位、定向方法。采用惯性导航系统获取掘进机实时姿态信息,并传至激光感知系统与其检测光点特征信息相结合，利用空间坐标变换求解位置信息，回传惯导系统进行位姿辅助校准，通过融合各检测子系统的优缺点以实现掘进机的位姿精准检测，有效克服了单一惯性导航系统检测数值漂移、系统可靠性差等问题。最后，通过地面模拟检测试验和井下工业性试验，在不同工况下对检测系统的有效性和检测精度进行试验验证。结果表明：该组合定位系统横向偏移检测误差平均值小于10 mm，纵向行进检测误差平均值小于20 mm，能够满足不同工况下位姿检测的精度要求。研究将先进的信息融合技术引入煤矿开采科技，为煤巷综掘向无人化、智能化方向进一步发展提供理论指导和实践支撑。

In view of the environmental constraints such as long working cycle and large vibration amplitude during the cutting of the roadheader in the fully mechanized excavation face, it is difficult for a single inertial navigation system to realize autonomous, real-time and accurate perception of the attitude and position of the roadheader in the fully mechanized excavation process due to the influence of navigation error accumulation with time. Taking the inertial navigation system as the main system, a combined positioning and orientation method based on inertial navigation system and laser sensing system is proposed. The inertial navigation system is used to obtain the real-time attitude information of the roadheader, which is transmitted to the laser sensing system and combined with its detection light point feature information. The spatial coordinate transformation is used to solve the position information, and the inertial navigation system is transmitted back to the inertial navigation system for pose auxiliary calibration. By integrating the advantages and disadvantages of each detection subsystem, the accurate detection of the pose of the roadheader is realized, which effectively overcomes the problems of single inertial navigation system detection value drift and poor system reliability. Finally, through the ground simulation test and the underground industrial test, the effectiveness and detection accuracy of the detection system are verified under different working conditions. The results show that the average error of the lateral offset detection of the integrated positioning system is less than 10 mm, and the average error of the longitudinal detection is less than 20 mm, which can meet the accuracy requirements of the lower position detection under different working conditions. The introduction of advanced information fusion technology into coal mining technology provides theoretical guidance and practical support for the further development of unmanned and intelligent coal roadway excavation.