In recent years, mobile robots have been widely used in various fields such as emergency rescue, public security, inspection and detection. In the process of robot movement, the ability to perceive the environment is particularly important, especially in outdoor wide area work scenes involving dynamic, unknown, and complex factors. Obstacle detection greatly affects the functionality and efficiency of the robot. A comparison was made on the research progress of obstacle detection for ground mobile robots in such scenarios, and positive and negative obstacle detection methods were analyzed based on the characteristics of obstacles. Furthermore, the current application status of information fusion and deep learning in the current field was summarized. Finally, the current research status in the field of obstacle detection was summarized, and the exploration direction of related technologies was pointed out.