FUSION SPARSE AND SHAPING REWARD FUNCTION IN SOFT ACTOR-CRITIC DEEP REINFORCEMENT LEARNING FOR MOBILE ROBOT NAVIGATION

Abu Bakar, Mohamad Hafiz and Shamsudin, Abu Ubaidah and Soomro, Zubair Adil and Tadokoro, Satoshi and Salaan, C. J (2024) FUSION SPARSE AND SHAPING REWARD FUNCTION IN SOFT ACTOR-CRITIC DEEP REINFORCEMENT LEARNING FOR MOBILE ROBOT NAVIGATION. Jurnal Teknologi, 86 (2). pp. 1-13. ISSN 2180–3722

Text J17155_fee1ae5af82031f5ee1f764afb29b8db.pdf Restricted to Registered users only Download (1MB) | Request a copy

Abstract

Nowadays, the advancement in autonomous robots is the latest influenced by the development of a world surrounded by new technologies. Deep Reinforcement Learning (DRL) allows systems to operate automatically, so the robot will learn the next movement based on the interaction with the environment. Moreover, since robots require continuous action, Soft Actor Critic Deep Reinforcement Learning (SAC DRL) is considered the latest DRL approach solution. SAC is used because its ability to control continuous action to produce more accurate movements. SAC fundamental is robust against unpredictability, but some weaknesses have been identified, particularly in the exploration process for accuracy learning with faster maturity. To address this issue, the study identified a solution using a reward function appropriate for the system to guide in the learning process. This research proposes several types of reward functions based on sparse and shaping reward in SAC method to investigate the effectiveness of mobile robot learning. Finally, the experiment shows that using fusion sparse and shaping rewards in the SAC DRL successfully navigates to the target position and can also increase accuracy based on the average error result of 4.99%.

Item Type:	Article
Uncontrolled Keywords:	Soft Actor Critic Deep Reinforcement Learning (SAC DRL), Deep Reinforcement Learning, Mobile robot navigation, Reward function, Sparse reward, Shaping reward
Subjects:	T Technology > TJ Mechanical engineering and machinery
Divisions:	Faculty of Electrical and Electronic Engineering > FKEE
Depositing User:	Mr. Mohamad Zulkhibri Rahmad
Date Deposited:	10 Jan 2025 08:03
Last Modified:	10 Jan 2025 08:05
URI:	http://eprints.uthm.edu.my/id/eprint/11759

Actions (login required)

View Item