AURUM Mühendislik Sistemleri ve Mimarlık Dergisi

Yazarlar: Omar YASEEN MAHMOOD, Osman Nuri UÇAN, Oğuz BAYAT

Konular:Bilgisayar Bilimleri, Bilgi Sistemleri

Anahtar Kelimeler:Robotics,Artificial Neural Networks,Reinforcement Learning,Light Detection and Ranging

Özet: Robots are being used to automate several tasks in different environments. Some of these applications require the robots to be able to navigate in complex environments and avoid obstacles to reach their destinations. According to the dynamic nature of these environments, Artificial Intelligence (AI) is being used to allow robots handle continuously-changing environments. The existing techniques require intensive processing power and energy sources, which limits their employment is many applications. Thus, a new method is proposed in this study to take control of the robot when a collision is predicted. Different representations of the environment are used, so that, historical information can be provided efficiently. However, the results show that the use of the entire batch has better performance with similar complexity. The proposed method has been able to reduce the number of collision and increasing the speed of the robot during the navigation.

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