Evolutionary Techniques for Mobile Robot Navigation

Abstract:

Current research trend in mobile robot is to build intelligent and autonomous systems that enables mobile robot to plan its motion in static and dynamic environment. In this paper, Genetic Algorithm (GA) is utilized to come out with an algorithm that enables the mobile robot to move from the starting position to the desired goal without colliding with any of the obstacles in the environment. The proposed navigation technique is capable of re-planning new optimum collision free path in the event of mobile robot encountering dynamic obstacles. The method is verified using MATLAB simulation and validated by Team AmigoBotTM robot. The results obtained from MATLAB simulation and real time implementation are discussed at the end of the paper.

• Periodical: Advanced Materials Research (Volumes 433-440)
• Pages: 6646-6651
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.433-440.6646
• Online since: January 2012
• Authors: Soh Chin Yun, S. Parasuraman, Velappa Ganapathy
• Keywords: Genetic Algorithm (GA), Genetic Controller, Goal Oriented Path Planning Algorithm (GOPPA), MATLAB, Path Planning, Team Amigobot^TM Robot

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