A real-time obstacle avoidance method for industrial vehicles based on binocular positioning and ranging is proposed to solve the problems of environmental influence and signal interference faced by the current obstacle avoidance technology of industrial vehicles. Firstly, the binocular depth camera is calibrated, and binocular stereo correction is performed on the images of the operating environment directly behind the vehicle. Secondly, the SGBM algorithm is used to calculate the parallax map, and the 3D point cloud reconstruction is carried out by the trigonometric transformation principle in combination with internal parameters of the camera. Next, the ground calibration and ground equation fitting are conducted, and the effective detection range and safety warning range are defined. Finally, the orientation of pedestrians is detected, and the distance calculation of pedestrians detected in the range is carried out by the algorithm of straight and turn ranging, and the range warning and obstacle avoidance are realized in real time. Four groups of experiments show that the errors of the pedestrian ranging algorithm are lower than 0.1 m and 0.2 m in 0–3 m and 3–5 m in straight and turning states, respectively. The identification accuracy of the pedestrian detection algorithm is 97.38%, and the detection frame rate is 22.12 fps. The method has high sensitivity within the set range and good real-time obstacle avoidance effects.