Compared with visual sensors,LIDAR has the advantages of strong anti-interference ability and high measurement accuracy.But it is difficult to make accurate measurements on the point cloud data which is sparse when multi-line LIDAR is far away from small obstacles.To solve the problem,YOLO (You Only Look Once) and HSV spatial color histogram matching are combined to perform long-range target detection.In the process of robot motion,when the amount of laser data in the detection area meets the requirements,the LIDAR data at this time is clustered,the feature points are extracted,and the key parameters are calculated based on the sensor calibration results,so as to complete the measurement of obstacles.A 16-line Velodyne LIDAR and an industrial IDS camera are used for verification of the method.The results show that this method can increase the data volume of LIDAR by up to 7.83 times.Even in motion scenes,it is guaranteed that the maximum width error of small obstacles is less than 2.4%,and the distance-measuring error is less than 0.15%.