Abstract
Ant colony optimization (ACO) technique is proposed to solve the mobile robot path planning (MRPP) problem. In order to demonstrate the effectiveness of ACO in solving the MRPP problem, several maps of varying complexity used by an earlier researcher is used for evaluation. Each map consists of static obstacles in different arrangements. Besides that, each map has a grid representation with an equal number of rows and columns. The performance of the proposed ACO is tested on a given set of maps. Overall, the results demonstrate the effectiveness of the proposed approach for path planning.
| Original language | English |
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| Title of host publication | 2016 2nd IEEE International Symposium on Robotics and Manufacturing Automation, ROMA 2016 |
| Publisher | IEEE, Institute of Electrical and Electronics Engineers |
| ISBN (Electronic) | 9781509009282 |
| DOIs | |
| Publication status | Published - 2017 |
| Event | IEEE International Symposium on Robotics and Manufacturing Automation 2016 - Ipoh, Malaysia Duration: 25 Sept 2016 → 27 Sept 2016 Conference number: 2nd https://ieeexplore.ieee.org/xpl/conhome/7838013/proceeding (Proceedings) |
Conference
| Conference | IEEE International Symposium on Robotics and Manufacturing Automation 2016 |
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| Abbreviated title | ROMA 2016 |
| Country/Territory | Malaysia |
| City | Ipoh |
| Period | 25/09/16 → 27/09/16 |
| Internet address |
Keywords
- Ant Colony Optimization
- Mobile Robot
- Path Planning