Citation

Muhamad Amin, Anang Hudaya and Ahmad, Nazrul Muhaimin and Sayeed, Md. Shohel and Khan, Asad I. (2014) Learning above-and-below relationship for vision-based robot navigation system using Distributed Hierarchical Graph Neuron (DHGN) algorithm. In: 2014 13th International Conference on Control Automation Robotics & Vision (ICARCV). IEEE, pp. 595-600. ISBN 978-1-4799-5199-4

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Abstract

Obstacle avoidance is one of the important considerations in developing a vision-based robot navigation system. For flying robots, the ability to learn the above-and-below relationship for obstacle avoidance is necessary. This paper presents a conceptual work in developing a learning mechanism to identify the above-and-below relationship for obstacle avoidance in vision-based robot navigation system using a pattern recognition algorithm known as Distributed Hierarchical Graph Neuron (DHGN). DHGN is a bio-inspired pattern recognition algorithm that implements learning and memorization through a distributed and hierarchical processing. Preliminary results of simple above-and-below navigation with binary images using DHGN indicate that the scheme is able to produce high recall accuracy for obstacle detection. In addition, the proposed scheme implements a one-shot learning approach that is suitable for realtime deployment in robot navigation system.

Item Type:	Book Section
Subjects:	Q Science > QA Mathematics > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science T Technology > T Technology (General)
Divisions:	Faculty of Information Science and Technology (FIST)
Depositing User:	Ms Nurul Iqtiani Ahmad
Date Deposited:	27 Apr 2015 08:27
Last Modified:	28 Apr 2015 01:51
URII:	http://shdl.mmu.edu.my/id/eprint/6202

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