Real-Time Obstacle Avoidance Based on Floor Detection for Mobile Robots

Adem HİÇDURMAZ; Adem TUNCER

doi:https://doi.org/10.16984/saufenbilder.674122

Makale detayları

Real-Time Obstacle Avoidance Based on Floor Detection for Mobile Robots

Yazarlar:

Adem HİÇDURMAZ | Adem TUNCER

Ana Başlıklar:

Veri işleme & bilgisayar bilimi

Dergi:

Sakarya University Journal of Science 2020 Vol.24 Issue 5, pp.845-853

Belge Tipi:

Makale

Yayın Tarihi:

9/2020

Belge Dili:

İngilizce

Document ID (Org No.):

2000556645

DOI:

https://doi.org/10.16984/saufenbilder.674122

Özet:

 

Obstacle detection and avoidance are two main problems that demand solutions in the autonomous movement of mobile robots. To this end, the robots have been equipped with sensors and cameras. This study proposes a new method that allows mobile robots to move freely without any collision in an uncertain (i.e., both static and dynamic) workspace by processing images taken using a real-time webcam. In the study, a robot was allowed to move depending on the visibility and suitability of the floor in the images. These steps were repeated for each new image and, furthermore, the images were segmented based on an adaptive threshold obtained by calculating the statistical parameters. This segmentation was aimed to separate the floor from other areas in the study. Experimental results demonstrate that the proposed method is extremely successful to separate the floor from other regions and has a low cost and flexible method for obstacle avoidance.

Makale detayları

Real-Time Obstacle Avoidance Based on Floor Detection for Mobile Robots

Yazarlar: Adem HİÇDURMAZ | Adem TUNCER

Ana Başlıklar: Veri işleme & bilgisayar bilimi

Dergi: Sakarya University Journal of Science 2020 Vol.24 Issue 5, pp.845-853

Belge Tipi: Makale

Yayın Tarihi: 9/2020

Belge Dili: İngilizce

Document ID (Org No.): 2000556645

DOI: https://doi.org/10.16984/saufenbilder.674122

Sayı

Yazarlar:

Adem HİÇDURMAZ | Adem TUNCER

Ana Başlıklar:

Veri işleme & bilgisayar bilimi

Dergi:

Sakarya University Journal of Science 2020 Vol.24 Issue 5, pp.845-853

Belge Tipi:

Makale

Yayın Tarihi:

9/2020

Belge Dili:

İngilizce

Document ID (Org No.):

2000556645

DOI:

https://doi.org/10.16984/saufenbilder.674122