A Doorway Detection and Direction (3Ds) System for Social Robots via a Monocular Camera

In this paper, we propose a novel algorithm to detect a door and its orientation in indoor settings from the view of a social robot equipped with only a monocular camera. The challenge is to achieve this goal with only a 2D image from a monocular camera. The proposed system is designed through the i...

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Bibliographic Details
Published in:Sensors (Basel, Switzerland) Switzerland), 2020-04, Vol.20 (9), p.2477
Main Authors: Othman, Kamal M, Rad, Ahmad B
Format: Article
Language:English
Subjects:
2D image
Advantages
Algorithms
Cameras
Computer simulation
doorway detection
doorway direction
Indoor environments
Lasers
Localization
Machine learning
Medical research
Methods
monocular camera
Nao humanoid robot
Navigation systems
Robotics
Robots
Sensors
social robot
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Summary:In this paper, we propose a novel algorithm to detect a door and its orientation in indoor settings from the view of a social robot equipped with only a monocular camera. The challenge is to achieve this goal with only a 2D image from a monocular camera. The proposed system is designed through the integration of several modules, each of which serves a special purpose. The detection of the door is addressed by training a convolutional neural network (CNN) model on a new dataset for Social Robot Indoor Navigation (SRIN). The direction of the door (from the robot's observation) is achieved by three other modules: Depth module, Pixel-Selection module, and Pixel2Angle module, respectively. We include simulation results and real-time experiments to demonstrate the performance of the algorithm. The outcome of this study could be beneficial in any robotic navigation system for indoor environments.
ISSN:1424-8220
1424-8220
DOI:10.3390/s20092477