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Modified Q-learning with distance metric and virtual target on path planning of mobile robot

Path planning is an essential element in mobile robot navigation. One of the popular path planners is Q-learning – a type of reinforcement learning that learns with little or no prior knowledge of the environment. Despite the successful implementation of Q-learning reported in numerous studies,...

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Main Authors: Ee, Soong Low, Ong, Pauline, Cheng, Yee Low, Omar, Rosli
Format: Article
Language:English
Published: Elsevier 2020
Subjects:
T Technology (General)
Online Access:http://eprints.uthm.edu.my/7147/1/J14146_d4792edcf485886c4b01ef6a4fbc4dca.pdf
http://eprints.uthm.edu.my/7147/
https://doi.org/10.1016/j.eswa.2022.117191
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spelling my.uthm.eprints.71472022-06-14T02:08:43Z http://eprints.uthm.edu.my/7147/ Modified Q-learning with distance metric and virtual target on path planning of mobile robot Ee, Soong Low Ong, Pauline Cheng, Yee Low Omar, Rosli T Technology (General) Path planning is an essential element in mobile robot navigation. One of the popular path planners is Q-learning – a type of reinforcement learning that learns with little or no prior knowledge of the environment. Despite the successful implementation of Q-learning reported in numerous studies, its slow convergence associated with the curse of dimensionality may limit the performance in practice. To solve this problem, an Improved Q-learning (IQL) with three modifications is introduced in this study. First, a distance metric is added to Q-learning to guide the agent moves towards the target. Second, the Q function of Q-learning is modified to overcome dead-ends more effectively. Lastly, the virtual target concept is introduced in Q-learning to bypass dead-ends. Experi�mental results across twenty types of navigation maps show that the proposed strategies accelerate the learning speed of IQL in comparison with the Q-learning. Besides, performance comparison with seven well-known path planners indicates its efficiency in terms of the path smoothness, time taken, shortest distance and total distance used. Elsevier 2020 Article PeerReviewed text en http://eprints.uthm.edu.my/7147/1/J14146_d4792edcf485886c4b01ef6a4fbc4dca.pdf Ee, Soong Low and Ong, Pauline and Cheng, Yee Low and Omar, Rosli (2020) Modified Q-learning with distance metric and virtual target on path planning of mobile robot. Expert Systems with Applications, 199. ISSN 0957-4174 https://doi.org/10.1016/j.eswa.2022.117191
institution Universiti Tun Hussein Onn Malaysia
building UTHM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tun Hussein Onn Malaysia
content_source UTHM Institutional Repository
url_provider http://eprints.uthm.edu.my/
language English
topic T Technology (General)
spellingShingle T Technology (General)
Ee, Soong Low
Ong, Pauline
Cheng, Yee Low
Omar, Rosli
Modified Q-learning with distance metric and virtual target on path planning of mobile robot
description Path planning is an essential element in mobile robot navigation. One of the popular path planners is Q-learning – a type of reinforcement learning that learns with little or no prior knowledge of the environment. Despite the successful implementation of Q-learning reported in numerous studies, its slow convergence associated with the curse of dimensionality may limit the performance in practice. To solve this problem, an Improved Q-learning (IQL) with three modifications is introduced in this study. First, a distance metric is added to Q-learning to guide the agent moves towards the target. Second, the Q function of Q-learning is modified to overcome dead-ends more effectively. Lastly, the virtual target concept is introduced in Q-learning to bypass dead-ends. Experi�mental results across twenty types of navigation maps show that the proposed strategies accelerate the learning speed of IQL in comparison with the Q-learning. Besides, performance comparison with seven well-known path planners indicates its efficiency in terms of the path smoothness, time taken, shortest distance and total distance used.
format Article
author Ee, Soong Low
Ong, Pauline
Cheng, Yee Low
Omar, Rosli
author_facet Ee, Soong Low
Ong, Pauline
Cheng, Yee Low
Omar, Rosli
author_sort Ee, Soong Low
title Modified Q-learning with distance metric and virtual target on path planning of mobile robot
title_short Modified Q-learning with distance metric and virtual target on path planning of mobile robot
title_full Modified Q-learning with distance metric and virtual target on path planning of mobile robot
title_fullStr Modified Q-learning with distance metric and virtual target on path planning of mobile robot
title_full_unstemmed Modified Q-learning with distance metric and virtual target on path planning of mobile robot
title_sort modified q-learning with distance metric and virtual target on path planning of mobile robot
publisher Elsevier
publishDate 2020
url http://eprints.uthm.edu.my/7147/1/J14146_d4792edcf485886c4b01ef6a4fbc4dca.pdf
http://eprints.uthm.edu.my/7147/
https://doi.org/10.1016/j.eswa.2022.117191
_version_ 1738581582368735232
score 13.244368

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