AI-Powered Drone Integration for Obstacle Avoidance

A tétel rövid nézete
dc.contributor.advisorKorsoveczki, Gyula
dc.contributor.authorAlTamimi, Jebril
dc.contributor.departmentDE--Műszaki Kar
dc.date.accessioned2023-12-20T13:28:01Z
dc.date.available2023-12-20T13:28:01Z
dc.date.created2023-12-01
dc.description.abstractThis article discusses how drones are transforming various industries, such as agriculture and surveillance, yet they still face difficulties in autonomously navigating complex environments. To address this, the article introduces a method that combines artificial intelligence (AI) with drone systems to enhance their ability to avoid obstacles. The approach involves the use of deep reinforcement learning (DRL) techniques to better the navigation skills of drones. The authors detail their integrated hardware and software strategy, emphasizing their preliminary findings and the obstacles they encountered. The primary aim of this research is to further the use of autonomous drones in real-life situations.
dc.description.courseMechatronical Engineeringen
dc.description.degreeBSc/BA
dc.format.extent86
dc.identifier.urihttps://hdl.handle.net/2437/364139
dc.language.isoen
dc.rights.accessHozzáférhető a 2022 decemberi felsőoktatási törvénymódosítás értelmében.
dc.subjectDeep Reinforcement Learning (DRL)
dc.subjectVirtual Environment
dc.subjectSimulation Environment
dc.subjectTwin-Delayed Deep Deterministic Policy Gradient(TD3)
dc.subject.dspaceDEENK Témalista::Engineering Sciences::Electrical Engineering
dc.subject.dspaceDEENK Témalista::Engineering Sciences::Engineering
dc.titleAI-Powered Drone Integration for Obstacle Avoidance
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Theses (Department of Electrical Engineering and Mechatronics)