GA-based Path Planning for Mobile Robots: An Empirical Evaluation of Seven Techniques
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| Title | GA-based Path Planning for Mobile Robots: An Empirical Evaluation of Seven Techniques |
| Authors | |
| Abstract | Previous research suggests that genetic algorithms (GAs) offer a promising solution to path planning for mobile robots. We examine six simple GAs used in prior studies, comparing them to a new node sequence approach that includes a two-step fitness function. Through a series of repeated trials using a simple 16x16 grid, a 100x100 grid, a 600x600 Mars landscape, and a complex maze-like environment, we compare the chromosome structures and fitness functions of these seven methods. The results of our empirical testing indicate that the proposed dual goal approach, which uses a fixed length chromosome structure, outperformed both monotonic and other node sequence approaches, consistently finding a feasible path in even the most challenging of these environments. |
| Publisher | ACADEMY PUBLISHER |
| Date | 2013-08-01 |
| Source | Journal of Computers Vol 8, No 8 (2013) |
| Rights | Copyright © ACADEMY PUBLISHER - All Rights Reserved.To request permission, please check out URL: http://www.academypublisher.com/copyrightpermission.html. |