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...

Full description

Saved in:
Bibliographic Details
Main Author: Nang Yune Thitsar
Other Authors: Hu Guoqiang
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2022
Subjects:
Online Access:https://hdl.handle.net/10356/158511
Tags: Add Tag
No Tags, Be the first to tag this record!
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