Abstract
In this thesis, the goal is to design a navigation system for an mobile robot by a scanning laser rangefinder and the encoders built in the robot to sense the environmental variation during robot maneavering. To locate the position of the robot, the environmental map and the information of the initial position must be known as a priori. An algorithm of features extraction is thus developed to extract the corner landmarks from the environment scan to estimate the translation and rotation between consecutive scanning data, then correct the error produced by the encoders due to wheels slipping. The location of these particular features is considered to be invariant as compared to the vehicle. They can therefore be used as stable and reliable landmarks in a localization algorithm. And the real-time scanning data can be also used for obstacles avoidance. A wheeled-robot will be adopted as the navigation vehicle, and the whole system will be tested within an unknown environment to validate the performance of the proposed navigation system.