计算机工程与应用 ›› 2020, Vol. 56 ›› Issue (13): 164-171.DOI: 10.3778/j.issn.1002-8331.1903-0346

• 模式识别与人工智能 • 上一篇    下一篇

基于轮式机器人的实时3D栅格地图构建

刘安睿劼,王耀力   

  1. 太原理工大学 信息与计算机学院,太原 030024
  • 出版日期:2020-07-01 发布日期:2020-07-02

Real-Time 3D Grid Map Construction Based on Wheeled Robot

LIU Anruijie, WANG Yaoli   

  1. School of Information and Computer Science, Taiyuan University of Technology, Taiyuan 030024, China
  • Online:2020-07-01 Published:2020-07-02

摘要:

移动机器人在各种任务中需要进行建图、定位和路径规划,但是目前的视觉SLAM只能输出相机的运动轨迹图,而不能生成用于路径规划和导航的地图。因此,在ORB_SLAM2的基础上,与RGB-D相机相结合,提出了一种实时3D栅格地图构建算法。建立了一个逆传感器模型(Inverse Sensor Model,ISM);针对ISM模型,重新构建了3D栅格地图的算法;联合ORB_SLAM2进行数据集实验、仿真环境实验和实时构建实验。经实验验证,该算法能够利用ORB_SLAM2实时构建出具有尺度的3D栅格地图,且能够清晰地显示障碍物位置,验证了该算法的有效性。

关键词: ORB_SLAM2系统, RGB-D相机, 逆传感器模型(ISM), 3D栅格地图

Abstract:

Mobile robots in a variety of tasks need to be built in map, location and path planning, but the current vision SLAM can only output camera trajectory map, but cannot generate a route planning and navigation maps. Therefore, this paper proposes a real-time 3D raster map construction algorithm, based on the ORB_SLAM2, combined with RGB-D camera. An Inverse Sensor Model(ISM) is first established. Secondly, the algorithm of 3D grid map is reconstructed for the ISM model. Finally, it combines with ORB_SLAM2 for data set experiments, simulation environment experiments and real-time construction experiments. The experimental results show that the algorithm can construct a 3D grid map with scale in real time by using ORB_SLAM2, and can clearly display the obstacle position, and verify the effectiveness of the algorithm.

Key words: ORB_SLAM2, RGB-D camera, Inverse Sensor Model(ISM), 3D grid map