For bad real-time ability and poor accuracy rate of the monocular obstacle avoidance algorithm for quad-rotor helicopters in practical engineering applications, a new monocular obstacle avoidance algorithm based on Pyramid Lucas-Kanade optical flow and moving optical flow was proposed and the mathematical derivation process of the algorithm was given. The algorithm was established and implemented on a ArduCopter quad-rotor helicopter equipped with a 320 pixel×240 pixel camera and many experiments was done to verify the feasibility and effectiveness of the algorithm. In the process of vehicle autonomous flight, the vanishing points were used for navigation and a neural net PID was used to control flighting adaptively. As compared with the monocular Synchronous Location Mapping(SLAM) obstacle avoidance algorithm, Horn-Schunck optical flow obstacle avoidance algorithm and the image segmentation obstacle avoidance algorithm, the proposed algorithm shows better real-time ability and accuracy rate, and can meet the requirements of obstacle avoidance in real time for quad-rotor helicopters.