Real time object detection methods are useful in assessing different situation like theft, military activities, health care sectors etc. YOLO is one of the fastest deep learning techniques for object detection. In this research study comprehensive survey is done for different versions of YOLO object detection technique which is very popular nowadays. YOLO version 1 to 8 is surveyed in this research study; comparative study is done based on dataset used, YOLO architecture, mAP achieved, strength and limitation. the major changes done in architecture is also elaborated in this research study.