Intelligent robots are usually used in tunnel safety inspection and emergency rescue of coal mine disaster environments.At present, the technology of autonomous navigation and obstacle avoidance of intelligent robot is relatively mature, but the main application scenarios are outdoor environments with satellite positioning(GPS, Beidou navigation system etc.)or special indoor environments.For the complex environment of coal mine tunnel with uneven illumination and narrow underground space, the autonomous navigation method of intelligent robot in coal mine tunnel needs further research.The commonly used traditional inertial navigation applies the acceleration and angular velocity of an inertial measurement unit(IMU)to estimate the position information of the object in 3-D space, but its error accumulation problem is more serious.There are a large number of pipelines arranged in coal mine tunnel, and their structured features are very remarkable.The image of coal mine tunnel is obtained through the onboard camera, then the machine vision algorithm is constructed to locate the pipeline in the tunnel images, consequently, the robot’s vision navigation is assisted by solving the yaw angle between the robot and the pipeline above mentioned.In view of the bright colors and the obvious geometric shape characteristics of the pipeline in coal mine tunnel, this paper combines the color and geometric characteristics and divides the image into multiple independent sub-images longitudinally to reduce the impact of environmental noise on the pipeline segmentation in the image, and then obtain candidate pipeline contours from each sub-image, and the contours are grouped according to whether they belong to the same pipeline.From each group of candidate contours, a more robust and stable pipeline contour is further selected based on the parallelism of the straight line fitted by the pipeline contours.Combined with the camera pinhole model and the yaw angle calculation model in this paper, the current yaw angle of the robot is obtained.Experiments show that the method proposed in this paper was not only fast, but also the calculated yaw angle in an accurate and reliable way, which can meet the needs of vision-aided positioning and navigation of coal mine tunnel robot.
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