Realtime Corridor Detection for Mobile Robot Navigation with Hough Transform Using a Depth Camera

Abstract

The ability to detect corridor-like structures is essential for autonomous mobile robot navigation in indoor environments. In this paper, we present a novel method for real-time corridor detection using a single depth camera. Our aim is to find a corridor just by looking at walls, even if there are some objects inside, such as a trash can or a chair. Once the corridor has been determined, the robot can be moved smoothly along the hallway semi-autonomously with simple commands without hitting the walls. The proposed work combines layers of occupancy-maps extracted from Point Cloud into one final occupancy grid-map, where 2D Hough Transform is applied to extract the lines corresponding to the corridor walls. The method has been tested on a real-robot using Mynt-eye depth camera. The experimental results show the reliability and efficiency of the proposed technique for navigation tasks in corridor-like unknown environments.