Optimizing mobile robot navigation through neuro-symbolic fusion of Deep Deterministic Policy Gradient (DDPG) and fuzzy logic

Nasary, Muhammad Faqiihuddin and Mohd Ibrahim, Azhar and Al Mahmud, Suaib and Shafie, Amir Akramin and Mardzuki, Muhammad Imran (2024) Optimizing mobile robot navigation through neuro-symbolic fusion of Deep Deterministic Policy Gradient (DDPG) and fuzzy logic. In: 4th International Conference on Robotics, Computer Vision and Intelligent Systems, ROBOVIS 2024, 25-27 February 2024, Rome, Italy.

	PDF - Published Version Restricted to Repository staff only Download (1MB)
Preview	PDF - Published Version Download (92kB) | Preview
	PDF - Accepted Version Restricted to Registered users only Download (1MB)

Abstract

Mobile robot navigation has been a sector of great importance in the autonomous systems research arena for a while. For ensuring successful navigation in com-plex environments several rule-based traditional approaches have been employed previously which possess several drawbacks in terms of ensuring navigation and obstacle avoidance efficiency. Compared to them, reinforcement learning is a novel technique being assessed for this purpose lately. However, the constant re-ward values in reinforcement learning algorithms limits their performance capabil-ities. This study enhances the Deep Deterministic Policy Gradient (DDPG) algo-rithm by integrating fuzzy logic, creating a neuro-symbolic approach that imparts advanced reasoning capabilities to the mobile agents. The outcomes observed in the environment resembling real-world scenarios, highlighted remarkable perfor-mance improvements of the neuro-symbolic approach, displaying a success rate of 0.71% compared to 0.39%, an average path length of 35 meters compared to 25 meters, and an average execution time of 120 seconds compared to 97 sec-onds. The results suggest that the employed approach enhances the navigation performance in terms of obstacle avoidance success rate and path length, hence could be reliable for navigation purpose of mobile agents.

Item Type:	Proceeding Paper (Other)
Subjects:	T Technology > T Technology (General)
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Engineering > Department of Mechatronics Engineering
Depositing User:	Dr Azhar Mohd Ibrahim
Date Deposited:	02 Jul 2024 09:02
Last Modified:	02 Jul 2024 11:03
URI:	http://irep.iium.edu.my/id/eprint/112824

Actions (login required)

View Item