Vision-Based UAV Flight Control and Obstacle Avoidance

摘要

In this work, we explore various ideas and approaches to deal with the inherent uncertainty and image noise in motion analysis, and develop a low- complexity, accurate and reliable scheme to estimate the motion fields from UAV navigation videos. The motion field information allows us to accurately estimate ego-motion parameters of the UAV and refine (or correct) the motion measurements from other sensors. Based on the motion field information, we also compute the range map for objects in the scene. Once we have accurate knowledge about the vehicle motion and its navigation environment (range map), control and guidance laws can be designed to navigate the UAV between way points and avoid obstacles.