为了使仿人机器人能够在真实世界中自由行走，包括上下楼梯、跨过障碍物，本文提出了一种构建机器人环境的2.5维网格地图的方法。首先利用传感器数据建立并更新一个3D占有率网格和一个平地网格，3D占有率网格为最终的地图提供概率支持，以保证环境模型对传感器噪声的鲁棒性，平地网格用来存储平面高度值。然后结合两个网格建立导航地图，该地图上每一个单元格被标记为平地或障碍物类型以及它的高度值，平地的高度信息是精确的而障碍物的高度信息是粗略的。最后在仿真平台上验证了所提出的方法，仿真结果证实此方法能够有效地产生用于机器人避障和路径规划的地图。

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.