The inertial measurement unit (IMU) can achieve the advantages of autonomous full-parameter navigation and has the technical advantage of being applied in underground GPS-denied environments. The shearer positioning based on redundant IMUs is a feasible and low-cost positioning method for longwall mining equipment. However, it also faces the problem of a large drift of IMUs over time. When two IMUs are installed on the carrier of a coal mining machine, the differences in their respective output positions and attitudes should all be constants. They should meet the dual-IMU pose constraint conditions. Based on the constraints of position and attitude, a method for calculating the shearer double-IMU position and attitude is proposed based on the information filter. Taking the attitude quaternions of IMU-1 and IMU-2 as state quantities, the information filtering state equation is established based on the quaternion update equation. Using the raw output of the accelerometer, the raw output of the magnetometer, the position difference, and the attitude difference as the measurement values, the Jacobian matrices for converting the measurement values into attitude quaternions are derived, and the measurement equations are constructed. In the experiment of four cutting cycles, for IMU-1, the spherical probability errors (SPEs) of the third and fourth cutting cycles after processing by the algorithm are reduced from 3.618 0 m and 8.220 2 m to 3.618 0 m and 8.220 2 m. The positioning accuracy is improved by 64.9%. For IMU-2, the SPEs of the third and fourth cutting cycles after processing are reduced from 4.342 0 m and 5.736 8 m to 1.617 8 m and 2.352 3 m. The positioning accuracy is improved by 59.0%. The average values of the attitude angles processed by the IMU-1 and IMU-2 algorithms are obtained. The position coordinates of the mobile robot are calculated using the position estimation algorithm, and the SPEs of the third and fourth cuts are 0.790 7 m and 1.431 7 m, respectively. This method provides a low-level solution algorithm for redundant IMU positioning and improves positioning accuracy.