Learning above-and-below relationship for vision-based robot navigation system using Distributed Hierarchical Graph Neuron (DHGN) algorithm

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

[img] Text
Learning above-and-below relationship for vision-based robot navigation system using Distributed Hierarchical Graph Neuron (DHGN) algorithm.pdf
Restricted to Repository staff only

Download (349kB)
Official URL: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?...

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 > 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
URI: http://shdl.mmu.edu.my/id/eprint/6202

Actions (login required)

View Item View Item