Abstract
In this paper, we propose a method for travelable area detection in an urban environments using a LRF. Non-travel in the urban environment can be divided into roughly, change in the height and different materials. Our method using a laser range finder to get the reflection intensity and height information of the obstacles. The system recognizes using appropriate methods to observations obtained. Non-travel detection is edge points detection by the second order derivative using height information, and the classification by the machine learning using the reflection intensity. Afterwards, we construct a local environment map of the robot from detected results. The effectiveness of the proposed method is proved through the experiments results in outdoor environments.
