A visual navigation method of mobile robot based on hand-drawn route map and route is proposed.At first,some key boot points are picked up from the running path according to the principle of small deviation,so that the original path is divided into several segments.Then,during the mobile robot running along every segment,real-time image information from robot camera is matched with the corresponding one in the prior hand-drawn-route-map.In order to speeded up image processing,a kind of prediction estimation method is proposed to find the most potential image in the current field of vision. SURF(speed up robust feature) algorithm is used to detect image features.Matching points can be found rapidly in terms of KD-Tree.The projection transform matrix H between the referenced image and the real-time one is solved by RANSAC (RANdom SAmple Consensus) algorithm,in order to know the location of the referenced image in real-time one.With reference to odometer and real-time image information,the robot can be roughly localized.And then,for the next segment, the robot's running direction is computed according to its current rough localization until the last segment.At last,through a series of experiments,the advantage and efficiency of the new method in navigation and real-time dynamic obstacle avoidance are testified with the imprecise real map and route.