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dc.contributor.authorNang Yune Thitsaren_US
dc.identifier.citationNang Yune Thitsar (2022). Robot obstacle avoidance using reinforcement learning. Final Year Project (FYP), Nanyang Technological University, Singapore.
dc.description.abstractPath planning is one of the essential parts of the autonomous robotic field and cars. There are many paths planning algorithms use to solve the static environment. However, path planning for a dynamic environment is challenging in this robotic field. Some traditional path planning strategies pre-defined the robots' routes since the climate is already known. To face the dynamic environment, robots need to be more intelligent. Reinforcement learning is one of the machine learning techniques used to solve the dynamic environment and complex situations.en_US
dc.publisherNanyang Technological Universityen_US
dc.subjectEngineering::Electrical and electronic engineeringen_US
dc.titleRobot obstacle avoidance using reinforcement learningen_US
dc.typeFinal Year Project (FYP)en_US
dc.contributor.supervisorHu Guoqiangen_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.description.degreeBachelor of Engineering (Electrical and Electronic Engineering)en_US
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Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)
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