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Journals / Sakarya University Journal of Science / 2026 / Volume: 24 Issue: 5

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

Adem Hiçdurmaz(YALOVA ÜNİVERSİTESİ, FEN BİLİMLERİ ENSTİTÜSÜ, BİLGİSAYAR MÜHENDİSLİĞİ BÖLÜMÜ)0000-0001-7765-4529
Adem Tuncer(YALOVA ÜNİVERSİTESİ, MÜHENDİSLİK FAKÜLTESİ, BİLGİSAYAR MÜHENDİSLİĞİ BÖLÜMÜ)0000-0001-7305-1886
Pages
—
Publication Date
2020-10-01
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

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.

📌 3 Key Takeaways

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Objective & Hypothesis:Obstacle detection and avoidance are two main problems that demand solutions in the autonomous movement of mobile robots.
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Key Findings & Data:This segmentation was aimed to separate the floor from other areas in the study.
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Conclusion & Impact: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.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:mobile robot · obstacle avoidance · floor detection

Abstract

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.

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Cite This Article

Hiçdurmaz, A., Tuncer, A. (2020). Real-Time Obstacle Avoidance Based on Floor Detection for Mobile Robots. Sakarya University Journal of Science, Volume: 24 Issue: 5. https://doi.org/10.16984/saufenbilder.674122

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