Distributed visual navigation based on neural Q-learning for a mobile robot. (29th January 2007)

• Record Type: Journal Article
• Authors: Yang, Guosheng; Hou, Zeng-Guang; Liang, Zize
• Is Part Of: International journal of vehicle autonomous systems. Volume 4:Number 2/3/4(2006)
• Page Start: 225
• Page End: 238
• Publication Date: 2007-01-29
• Subjects: distributed visual navigation -- image processing -- mobile robots -- robot navigation -- Q-learning -- simulation -- vehicle autonomous systems -- autonomous vehicles -- neural networks -- fuzzy logic -- robot vision; Autonomous vehicles -- Periodicals; Motor vehicles -- Technological innovations -- Periodicals; Motor vehicles -- Electronic equipment -- Periodicals; Robots -- Control systems -- Periodicals; Intelligent transportation systems -- Periodicals; 629.20285
• Languages: English
• ISSNs: 1471-0226

Abstract

Distributed visual navigation based on neural Q-learning for a mobile robot is studied in this paper. First, a general distributed structure based on the multiple processors for visual navigation is established according to the decomposition of the mobile robot visual navigation task. Second, in terms of the general distributed structure, the local environment description method based on the Peer Group Filtering (PGF) and fuzzy technology is put forward. Third, in each local environment description, a controller based on neural Q-learning is designed to guide the mobile robot navigation. In the last part of this paper, experimental simulations are done to test the effectiveness of the presented distributed algorithm, including the image segmentation, environment description and navigation policy.