Slope detection based on orthogonal assumption

This paper presents a method to detect slope by using two-dimensional laser range finder (LRF) for robot navigation tasks in indoor environment. Considering the slope existing indoor environments, ordinary two-dimensional scanning map is not enough since the parameters of the slope and the condition of the floor also become extremely important for robot movement. In our research, one laser range finder (LRF1) is used for the regular horizontal scan while another one (LRF2) is used for the vertical scan. We extracted lines in each vertical scanning section in a rapid way and then distribute points into different classes based on the parameters of their corresponding lines. In order to simplify the algorithm of slope detection and parameters extraction, we introduce orthogonal assumption which supposes the environment around the slope is well structured so that walls and passageways are parallel or vertical to each other. Based on this reasonable assumption, we can extract all the required parameters of the floor and the slope from classified points in two-dimensional way. It is enough for robot navigation and the computational requirement is not high.