Real-time plane segmentation in a ROS-based navigation system for the visually impaired

Abstract

This paper provides a real-time plane segmentation method which can be used in navigation systems for the visually impaired to avoid indoor obstacles. The proposed method is based on surface normal estimation in range images. Efficiency and overall accuracy are considered as two main challenges in plane segmentation algorithms which use depth information. Our method exploits integral images to enhance the efficiency of normal estimation. A dynamic determination for smoothing region is proposed in our method to improve the overall accuracy. Compared to the methods in Point Cloud Library (PCL), our method consumes less time and has better performance in a wide range of depth (1∼8m). The proposed method is implemented on Robot Operating System (ROS) at 30fps. Our method makes it possible to obtain a robust and real-time indoor navigation system integrated with commercial Time-of-flight (TOF) sensors.