Obstacle avoidance with fuzzy logic controller
This study presents a simulated obstacle avoiding robot by fuzzy logic implementation. The basic goal of the simulated robot is to reach the target and avoid the obstacles along its path. The movement of the robot and avoidance characteristics is then guided by mathematical calculations fuzzyficatio...
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2010
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oai:animorepository.dlsu.edu.ph:faculty_research-98932023-04-11T05:53:27Z Obstacle avoidance with fuzzy logic controller Orillo, John William F. This study presents a simulated obstacle avoiding robot by fuzzy logic implementation. The basic goal of the simulated robot is to reach the target and avoid the obstacles along its path. The movement of the robot and avoidance characteristics is then guided by mathematical calculations fuzzyfication, and diffuzification. Also dynamic obstacles are included in the simulation to test the robustness and accuracy of the program. The speed, angle, and movement of the robot are dependent on FAM and the fuzzified data. The program is then simulated by using a graphical user interface done in c#. After several testing of the simulator the program showed 95% accuracy and thus concluded to be robust. 2010-01-01T08:00:00Z text https://animorepository.dlsu.edu.ph/faculty_research/8814 Faculty Research Work Animo Repository Robots—Control systems Fuzzy logic Electronics in navigation |
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De La Salle University |
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De La Salle University Library |
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Asia |
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Philippines Philippines |
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De La Salle University Library |
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DLSU Institutional Repository |
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Robots—Control systems Fuzzy logic Electronics in navigation |
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Robots—Control systems Fuzzy logic Electronics in navigation Orillo, John William F. Obstacle avoidance with fuzzy logic controller |
| description |
This study presents a simulated obstacle avoiding robot by fuzzy logic implementation. The basic goal of the simulated robot is to reach the target and avoid the obstacles along its path. The movement of the robot and avoidance characteristics is then guided by mathematical calculations fuzzyfication, and diffuzification. Also dynamic obstacles are included in the simulation to test the robustness and accuracy of the program. The speed, angle, and movement of the robot are dependent on FAM and the fuzzified data. The program is then simulated by using a graphical user interface done in c#. After several testing of the simulator the program showed 95% accuracy and thus concluded to be robust. |
| format |
text |
| author |
Orillo, John William F. |
| author_facet |
Orillo, John William F. |
| author_sort |
Orillo, John William F. |
| title |
Obstacle avoidance with fuzzy logic controller |
| title_short |
Obstacle avoidance with fuzzy logic controller |
| title_full |
Obstacle avoidance with fuzzy logic controller |
| title_fullStr |
Obstacle avoidance with fuzzy logic controller |
| title_full_unstemmed |
Obstacle avoidance with fuzzy logic controller |
| title_sort |
obstacle avoidance with fuzzy logic controller |
| publisher |
Animo Repository |
| publishDate |
2010 |
| url |
https://animorepository.dlsu.edu.ph/faculty_research/8814 |
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