CAD-Vision-Range-Based Self-Localization for Mobile Robot Using One Landmark

Localization is the process of determining the robot's posture within its environment including its current position and heading direction (or orientation). The process is of utmost importance for the autonomous navigational functions of a service robot. This paper describes a new localization method for service robots operating in a building based on a CAD model of the indoor environment in reasonable details. Only one specific landmark pasted within a specific region on the wall is needed. The camera with pan/tilt/zoom functions mounted on the robot first searches for this identification landmark and starts to conduct measurements using a laser rangefinder. With the polar coordinates of few measurement points on the wall and an accurate local CAD model, the exact position and orientation of the robot can be identified. This method has five distinctive advantages. First, the position of the landmark does not need to be precise. Second, each localization exercise is independent and no previous history of the moving track of the robot is required but the computational speed is still high. Third, the method is very robust with good fault-tolerance because it makes use of the reliable Hough transform. Fourth, the resolution is automatically adjusted because the panning resolution of the camera is based on the first effective measurement representing the distance of the robot from the landmark. Fifth, only the local CAD model of the room at the vicinity of the landmark needs a high precision because this model is used for localization. The system does not demand a highly accurate CAD model of the entire built environment. CAD models at other places are for navigation and path planning only.[PUBLICATION ABSTRACT]