Abstract:

In order that the humanoid robot can walk freely in the real world, including walking up and down stairs, climbing over small obstacles, a method of building a grid map of the robot’s surroundings is  proposed. At first the sensor data is used to build and update a 3D occupancy grid and a floor grid. The 3D occupancy grid provides the probabilistic support of the ultimate height map to keep robustness to sensor noise. The floor grid stores the height values of planar surfaces. Then a map for navigation is built under the combination of two grids. Each grid in the map is flagged with floor or obstacle and contains a value telling the height of the floor or the obstacle, and the height information of the floor is precise and that of the obstacle is coarse. Our approach is  verified on the platform of simulation and the result proves that the method is able to generate the map for path planning and collision avoidance.

Key words: map building;plane segmentation;floor grid;3D occupancy grid;navigation for robots