A two-layer navigation architecture for autonomous indoor exploration is proposed. As doors in the indoor environments are ubiquitous and informative for navigation, the high-level layer uses a stereo vision based algorithm to detect doors in order to generate a series of goal points. The low-level layer makes the robot avoid obstacles and navigate to the goal points by an improved dynamic window approach (DWA). This approach can solve the local-minima problem of DWA and can obtain smooth motion controls. The combination of high-level door-guidance and low-level goal-directed navigation enables the robot to make a door-to-door exploration. The proposed architecture was implemented on a Pioneer3 robot. Experiments show that the door detection algorithm and the improved DWA work reliably under various environments, and the robot can efficiently fulfill the task of autonomous indoor exploration.
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