Abstract

This paper proposes a method to extract on-line stable visual landmarks from sensory data obtained by stereo vision so as to adapt to changes of environment. Given a two-dimensional obstacle map, the robot first extracts vertical line segments which are distinct and inside planar surfaces not near boundary edges as they are expected to be observed reliably from various viewpoints. However, the extracted feature information such as position and length include uncertainty due to errors of vision and motion. The robot then reduces the uncertainty by matching the planar surface containing the features to the map. These processes are performed on-line in order to adapt to actual changes of lighting and the scene depending on the robot's view. Experimental results in real scenes show the validity of the proposed method.

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