Kinect depth image based door detection for autonomous indoor navigation

In this paper, an indoor navigation algorithm is proposed for the purpose of robot autonomous path planning. Due to the complex situation in indoor environments, it can cause a serious trouble for robot to identify the route during patrolling, especially for corner and door detection, which is the key step for intelligent navigation. To solve this problem, a kinect sensor is used for the door detection and corner location via depth images. The continuously varied ratios and depth difference in the images have been analyzed for the corner and door identification. Furthermore, the precise position of the doors and corners can be localized via the 3-dimensional characteristics of the depth images. Experiments in different scenarios have been performed to verify the efficacy of the algorithm for robot indoor autonomous navigation.