Potential collision detection method for underground locomotive operation based on YOLOV7
In the face of the complex environment during the operation of the underground mine unmanned electric locomotive,how to efficiently,quickly and accurately identify the potential collision bodies such as personnel and ore in the direction of the locomotive is of great significance to improve the efficiency of mine transportation and increase the economic benefits of the mine.As a relatively new and widely used algorithm of yolo series,the yolov7 algorithm has the characteristics of fast response speed,high accuracy,stable operation,etc.Therefore,this paper attempts to use the yolov7 algorithm to conduct potential collision body detection experiments.The test results show that the accuracy of the yolov7 algorithm meets the requirements,with mAP reaching 96.5%,and it can accurately detect potential colliders in low-light and long-distance environments.
万方数据
维普
