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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Alajlan, M. Koubaa, A. Chaari, I. Bennaceur, H. Ammar, A. |
| Copyright Year | 2013 |
| Description | Author affiliation: Res. Unit of Sci. & Technol, Al-Imam Mohamed bin Saud Univ., Saudi Arabia (Alajlan, M.; Bennaceur, H.; Ammar, A.) || PRINCE Res. Unit, Univ. of Manouba (ENSI), Manouba, Tunisia (Chaari, I.) || Coll. of Comput. & Inf. Sci., Prince Sultan Univ., Saudi Arabia (Koubaa, A.) |
| Abstract | Global path planning is considered as a fundamental problem for mobile robots. In this paper, we investigate the capabilities of genetic algorithms (GA) for solving the global path planning problem in large-scale grid maps. First, we propose a GA approach for efficiently finding an (or near) optimal path in the grid map. We carefully designed GA operators to optimize the search process. We also conduct a comprehensive statistical evaluation of the proposed GA approach in terms of solution quality, and we compare it against the well-known A* algorithm as a reference. Extensive simulation results show that GA is able to find the optimal paths in large environments equally to A* in almost all the simulated cases. |
| Sponsorship | IEEE Robot. Autom. Soc. |
| Starting Page | 1 |
| Ending Page | 8 |
| File Size | 662469 |
| Page Count | 8 |
| File Format | |
| ISBN | 9781479928132 |
| DOI | 10.1109/ICBR.2013.6729271 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2013-12-15 |
| Publisher Place | Tunisia |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Sociology Path planning Mobile robots Statistics Biological cells Genetic algorithms |
| Content Type | Text |
| Resource Type | Article |
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