A Doorway Detection and Direction (3Ds) System for Social Robots via a Monocular Camera
| Autor: | Ahmad B. Rad, Kamal Mohammed Othman |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
0209 industrial biotechnology
robotic control system Computer science SRIN dataset ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION convolutional neural network social robot 02 engineering and technology lcsh:Chemical technology 01 natural sciences Biochemistry Convolutional neural network Article Analytical Chemistry 020901 industrial engineering & automation lcsh:TP1-1185 Computer vision Electrical and Electronic Engineering Instrumentation Monocular camera Social robot business.industry Orientation (computer vision) 010401 analytical chemistry doorway detection Nao humanoid robot Atomic and Molecular Physics and Optics 0104 chemical sciences Robot doorway direction Artificial intelligence monocular camera depth information business 2D image |
| Zdroj: | Sensors Volume 20 Issue 9 Sensors, Vol 20, Iss 2477, p 2477 (2020) Sensors (Basel, Switzerland) |
| ISSN: | 1424-8220 |
| DOI: | 10.3390/s20092477 |
| Popis: | 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&rsquo 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. |
| Databáze: | OpenAIRE |
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