Robot obstacle avoidance using reinforcement learning

Path 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-def...

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Main Author:	Nang Yune Thitsar
Other Authors:	Hu Guoqiang
Format:	Final Year Project
Language:	English
Published:	Nanyang Technological University 2022
Subjects:	Engineering::Electrical and electronic engineering
Online Access:	https://hdl.handle.net/10356/158511
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Institution:	Nanyang Technological University
Language:	English

id	sg-ntu-dr.10356-158511
record_format	dspace
spelling	sg-ntu-dr.10356-1585112023-07-07T18:56:22Z Robot obstacle avoidance using reinforcement learning Nang Yune Thitsar Hu Guoqiang School of Electrical and Electronic Engineering GQHu@ntu.edu.sg Engineering::Electrical and electronic engineering Path 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. Bachelor of Engineering (Electrical and Electronic Engineering) 2022-06-03T04:24:57Z 2022-06-03T04:24:57Z 2022 Final Year Project (FYP) Nang Yune Thitsar (2022). Robot obstacle avoidance using reinforcement learning. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/158511 https://hdl.handle.net/10356/158511 en P1021-202 application/pdf Nanyang Technological University
institution	Nanyang Technological University
building	NTU Library
continent	Asia
country	Singapore Singapore
content_provider	NTU Library
collection	DR-NTU
language	English
topic	Engineering::Electrical and electronic engineering
spellingShingle	Engineering::Electrical and electronic engineering Nang Yune Thitsar Robot obstacle avoidance using reinforcement learning
description	Path 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.
author2	Hu Guoqiang
author_facet	Hu Guoqiang Nang Yune Thitsar
format	Final Year Project
author	Nang Yune Thitsar
author_sort	Nang Yune Thitsar
title	Robot obstacle avoidance using reinforcement learning
title_short	Robot obstacle avoidance using reinforcement learning
title_full	Robot obstacle avoidance using reinforcement learning
title_fullStr	Robot obstacle avoidance using reinforcement learning
title_full_unstemmed	Robot obstacle avoidance using reinforcement learning
title_sort	robot obstacle avoidance using reinforcement learning
publisher	Nanyang Technological University
publishDate	2022
url	https://hdl.handle.net/10356/158511
_version_	1772826631304380416

Robot obstacle avoidance using reinforcement learning

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