Knowledge base tuning using genetic algorithm for fuzzy behavior-based autonomous mobile robot
The attractive research in the field of robotics as a main alternative to conventional robot in recent years is Behavior-based mobile robot. This control architecture should generate perfect behavior action and able to handle conflicting actions that are seemingly irreconcilable, those are known as...
| Main Authors: | , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2005
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| Subjects: | |
| Online Access: | http://eprints.utm.my/1841/1/andi05_knowledgr_base_tuning.pdf |
| _version_ | 1796853312948011008 |
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| author | Adriansyah, Andi H. M. Amin, Shamsudin |
| author_facet | Adriansyah, Andi H. M. Amin, Shamsudin |
| author_sort | Adriansyah, Andi |
| collection | ePrints |
| description | The attractive research in the field of robotics as a main alternative to conventional robot in recent years is Behavior-based mobile robot. This control architecture should generate perfect behavior action and able to handle conflicting actions that are seemingly irreconcilable, those are known as Behaviour Design Problem and Action Selection Problem. This paper presents a new schema to overcome behavior-based problems based on Fuzzy Logic Controller (FLC) where the fuzzy knowledge bases are tuned automatically by Genetic Algorithm (GAs), known as Genetic Fuzzy System (GFS). The behaviors are controlled by GFS to generate individual command action. Later, a Context- Dependent Blending (DBD) based on meta fuzzy rules coordinates the commands to produce final control action. The scheme is validated using parameters of MagellanPro mobile robot and tested by simulation using MATLAB/ SIMULINK. Simulation results show that the proposed model offers hopeful advantages and has improved performance. |
| first_indexed | 2024-03-05T17:57:40Z |
| format | Conference or Workshop Item |
| id | utm.eprints-1841 |
| institution | Universiti Teknologi Malaysia - ePrints |
| language | English |
| last_indexed | 2024-03-05T17:57:40Z |
| publishDate | 2005 |
| record_format | dspace |
| spelling | utm.eprints-18412011-05-12T08:33:58Z http://eprints.utm.my/1841/ Knowledge base tuning using genetic algorithm for fuzzy behavior-based autonomous mobile robot Adriansyah, Andi H. M. Amin, Shamsudin TK Electrical engineering. Electronics Nuclear engineering The attractive research in the field of robotics as a main alternative to conventional robot in recent years is Behavior-based mobile robot. This control architecture should generate perfect behavior action and able to handle conflicting actions that are seemingly irreconcilable, those are known as Behaviour Design Problem and Action Selection Problem. This paper presents a new schema to overcome behavior-based problems based on Fuzzy Logic Controller (FLC) where the fuzzy knowledge bases are tuned automatically by Genetic Algorithm (GAs), known as Genetic Fuzzy System (GFS). The behaviors are controlled by GFS to generate individual command action. Later, a Context- Dependent Blending (DBD) based on meta fuzzy rules coordinates the commands to produce final control action. The scheme is validated using parameters of MagellanPro mobile robot and tested by simulation using MATLAB/ SIMULINK. Simulation results show that the proposed model offers hopeful advantages and has improved performance. 2005-12-05 Conference or Workshop Item NonPeerReviewed application/pdf en http://eprints.utm.my/1841/1/andi05_knowledgr_base_tuning.pdf Adriansyah, Andi and H. M. Amin, Shamsudin (2005) Knowledge base tuning using genetic algorithm for fuzzy behavior-based autonomous mobile robot. In: Proceeding of the 9th International Conference on Mechatronics Technology, 5-8 December 2005, Kuala Lumpur. |
| spellingShingle | TK Electrical engineering. Electronics Nuclear engineering Adriansyah, Andi H. M. Amin, Shamsudin Knowledge base tuning using genetic algorithm for fuzzy behavior-based autonomous mobile robot |
| title | Knowledge base tuning using genetic algorithm for fuzzy behavior-based autonomous mobile robot |
| title_full | Knowledge base tuning using genetic algorithm for fuzzy behavior-based autonomous mobile robot |
| title_fullStr | Knowledge base tuning using genetic algorithm for fuzzy behavior-based autonomous mobile robot |
| title_full_unstemmed | Knowledge base tuning using genetic algorithm for fuzzy behavior-based autonomous mobile robot |
| title_short | Knowledge base tuning using genetic algorithm for fuzzy behavior-based autonomous mobile robot |
| title_sort | knowledge base tuning using genetic algorithm for fuzzy behavior based autonomous mobile robot |
| topic | TK Electrical engineering. Electronics Nuclear engineering |
| url | http://eprints.utm.my/1841/1/andi05_knowledgr_base_tuning.pdf |
| work_keys_str_mv | AT adriansyahandi knowledgebasetuningusinggeneticalgorithmforfuzzybehaviorbasedautonomousmobilerobot AT hmaminshamsudin knowledgebasetuningusinggeneticalgorithmforfuzzybehaviorbasedautonomousmobilerobot |