Rapid Traversability Assessment in 2.5D Grid-based Map on Rough Terrain

This paper presents a rapid traversability assessment approach based on an extended 2.5D grid-based representaion of the rough terrain. Stereo vision system is used to perceive the environment surrounding robot. Conventional 2D, 3D and other 2.5D grid maps determine the traversability indices of the grids directly from the sensor feedback, while our approach attempts to address the indices of terrain from multiple grids instead. By analyzing the properties of multiple grids that the robot is to traverse, passable grids are distinguished, which also takes the robot’s size into account. Fuzzy logic framework is applied to extract traversabiltiy indices from the terrain characteristics. A soccer robot equipped with a stereo vision system is adopted for experiments. The results show that our map is capable of speeding the process of traversability assessment and providing an autonomous mobile robot with a appropriate representation of 3D uneven terrain profile.