K.H. Sedighi,∗ T.W. Manikas,∗∗ K. Ashenayi,∗∗∗ and R.L. Wainwright∗∗∗∗
Mobile robots, autonomous navigation, path planning, genetic algo- rithms
This paper demonstrates a new genetic algorithm approach for autonomous robot navigation that is based on a variable-monotone path representation. Many contemporary genetic algorithm methods assume that navigation follows a single-monotone path, where either the x or y coordinate of the path is always non-decreasing. While this approach allows for simple path representation structures, it can limit the success of finding a complete path through complex obstacle navigation environments. To address this limitation, this paper describes the development of a variable-monotone chromosome structure that allows for more flexibility in the navigation path, while still retaining the basic principles of the existing monotone chromosome structures. A genetic algorithm was developed using this new chromosome structure and tested on ten navigation spaces with varying obstacle complexity. The results show that the variable-monotone approach significantly outperformed the previous single-monotone approaches for navigating complex obstacle spaces.
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