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

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...

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Bibliographic Details
Main Authors: Saglam, A., Papelis, Y.
Format: Conference Proceeding
Language:English
Subjects:
Cameras
corridor detection
depth
Feature extraction
Hough Transform
mobile robot navigation
Navigation
obstacle avoidance
Point cloud compression
Point Clouds
Real-time systems
Robot vision systems
Transforms
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Summary: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.
ISSN:2642-3901
DOI:10.23919/ICCAS52745.2021.9649842