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Fuzzy Support Vector Machine-based Multi-agent Optimal Path Planning Approach to Robotics Environment.

Publication Type : Journal Article

Thematic Areas : TIFAC-CORE in Cyber Security

Publisher : Defence Science Journal

Source : Defence Science Journal, Volume 60, Issue 4, Number 4, p.387-391 (2010)

Url :

Campus : Coimbatore

School : Centre for Cybersecurity Systems and Networks, School of Engineering

Center : TIFAC CORE in Cyber Security

Department : Computer Science, Mathematics, cyber Security

Year : 2010

Abstract : A mobile robot to navigate purposefully from a start location to a target location, needs three basic requirements: sensing, learning, and reasoning. In the existing system, the mobile robot navigates in a known environment on a predefined path. However, the pervasive presence of uncertainty in sensing and learning, makes the choice of a suitable tool of reasoning and decision-making that can deal with incomplete information, vital to ensure a robust control system. This problem can be overcome by the proposed navigation method using fuzzy support vector machine (FSVM). It proposes a fuzzy logic-based support vector machine (SVM) approach to secure a collision-free path avoiding multiple dynamic obstacles. The navigator consists of an FSVM-based collision avoidance. The decisions are taken at each step for the mobile robot to attain the goal position without collision. Fuzzy-SVM rule bases are built, which require simple evaluation data rather than thousands of input-output training data. The effectiveness of the proposed method is verified by a series of simulations and implemented with a microcontroller for navigation.

Cite this Research Publication : Dr. Gireesh K. T., Poornaselvan, K. J., and Dr. M. Sethumadhavan, “Fuzzy Support Vector Machine-based Multi-agent Optimal Path Planning Approach to Robotics Environment.”, Defence Science Journal, vol. 60, no. 4, pp. 387-391, 2010.

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