Paper
16 October 2008 On a new approach to reduction of data for ANFIS application to unmanned robotic vehicles
Author Affiliations +
Proceedings Volume 7112, Unmanned/Unattended Sensors and Sensor Networks V; 711213 (2008) https://doi.org/10.1117/12.802590
Event: SPIE Security + Defence, 2008, Cardiff, Wales, United Kingdom
Abstract
A number of research workers have applied intelligent approaches for robotic applications. In the recent literature there is an increasing role of fuzzy and Neuro fuzzy approaches for unmanned vehicles. Both these approaches are based on intelligent rules. However for these applications the rules become very large and so computational time is very high. It is important to explore the approaches so as to reduce the computation time. In this paper a combination of factor analysis and clustering approaches is suggested so as to reduce the number of rules. The factor analysis can be used to reduce the number of parameters while clustering approach can be used to reduce the number of observations. Based on this methodology a new algorithm is developed which reduces the original parameters and observations into a set of new data. An algorithm is proposed and applied on a real robotic data available in a previous paper. Some of the applications for future work are proposed.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Harpreet Singh, Adam Mustapha, Shashank Kamthan, Arati M. Dixit, Deok Nam, Gary Witus, and Grant R. Gerhart "On a new approach to reduction of data for ANFIS application to unmanned robotic vehicles", Proc. SPIE 7112, Unmanned/Unattended Sensors and Sensor Networks V, 711213 (16 October 2008); https://doi.org/10.1117/12.802590
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KEYWORDS
Factor analysis

Sensors

Fuzzy logic

Classification systems

Statistical analysis

Infrared sensors

Fuzzy systems

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