Precise positioning method of tunneling machine for inertial navigation and visual information fusion

Abstract

For the difficulty of pinpointing of tunneling machines in the complex environment of coal mine tunnels,a precise positioning method of roadheader based on inertial navigation and visual fusion is proposed, which uses a positioning scheme of inertial navigation plus "vision+laser target". With the designed four feature point large-sized laser target fixed on the roof of the tunnel and the camera on the tunneling machine to collect laser target images, the scheme uses the circular fitting method to locate the center of the light spot and the EPnP algorithm based on four feature points to calculate the position of the tunneling machine. A “vision+laser target” position detection experiment was conducted in simulated condition of heading face to verify the effectiveness of the method in detecting the position of tunneling machines. The results are as follows: within 30 meters tunnel, the maximum error in the width, position, and height are no more than 28.549, 78.868, and 44.459 mm, which shows accurate detection of the position of the tunneling machine. For the inaccurate pose detection of tunneling machines in inertial navigation measurement, induced by the accumulation of pose errors over time and the machine vibration on the combined positioning system, an improved Sage-Husa adaptive filtering method for inertial navigation and visual information fusion is proposed, which could correct measurement errors by detecting new variance values to improve positioning accuracy. A combined positioning experiment of inertial navigation plus “vision+laser target” was conducted in a simulated heading face environment, using improved Sage-Husa adaptive filtering algorithm to fuse inertial navigation and visual information for comparative analysis, which show that the improved Sage-Husa adaptive filtering algorithm fusion results in smaller positioning errors. The maximum errors of pitch angle, roll angle, and heading angle are 0.029°, 0.051°, and 0.0113°, respectively. Within 30 meters, the position error of tunnel width is within the range of 0.033 m, and the position error of tunnel excavation direction is within the range of 0.062 m. Overall, the proposed inertial navigation plus visual fusion positioning method can meet the accuracy requirements of tunnel excavation positioning.

Keywords

• tunneling machine
• inertial navigation
• machine vision
• epnp
• sage-husa filtering