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publication name Non-Dominated Sorting Genetic Algorithm For Smooth Path Planning In Unknown Environments
Authors Hussein Shehata; Josef Schlattmann
year 2014
keywords Genetic Algorithm; Autonomous Navigation; Obstacle Avoidance
journal IEEE International Conference on Autonomous Robot Systems and Competitions (ROBÓTICA 2014)
volume Not Available
issue Not Available
pages 14-21
publisher IEEE
Local/International International
Paper Link http://ieeexplore.ieee.org/document/6849756/
Full paper download
Supplementary materials Not Available
Abstract

Autonomous robots have been the focus of attention of most researchers, particularly when it is imputed with terms like intelligence and autonomy. The most important challenge encounters autonomous navigation of a mobile robot is established from large amounts of uncertainties that are coupled with natural environment. This includes hazy and cloudy information of the environment. Moreover, continuous and fast changes of the real environment require a fast response from the robot. Many algorithms have been proposed and amongst these, the potential field algorithm is widely used. This work aims at optimizing some parameters involved in the potential field by the use of Non-Dominated Sorting Genetic Algorithm II (NSGA II). This paper takes into account the safety margin around the obstacle along with the size of the robot which also affects its motion during the optimization process in order to ensure the optimal path.

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