Mobile robot navigation using alpha level fuzzy logic system: Theoretical and experimental investigations
Numerous behavior rule selection mechanisms have been studied and examples of such mechanisms are discussed. Saffiotti (Saffiotti 2000) suggests dividing action selection mechanisms into two groups that he calls arbitration and command fusion which correspond to Mackenzie's (Mackenzie1999) stat...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Conference Paper |
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Curran Associates
2006
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| Online Access: | http://hdl.handle.net/20.500.11937/30154 |
| _version_ | 1848753006895431680 |
|---|---|
| author | Parasuraman, S. Ganapathy, V. Shirinzadeh, B. Zhong, Yongmin |
| author2 | Billingsley, John, ed. |
| author_facet | Billingsley, John, ed. Parasuraman, S. Ganapathy, V. Shirinzadeh, B. Zhong, Yongmin |
| author_sort | Parasuraman, S. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Numerous behavior rule selection mechanisms have been studied and examples of such mechanisms are discussed. Saffiotti (Saffiotti 2000) suggests dividing action selection mechanisms into two groups that he calls arbitration and command fusion which correspond to Mackenzie's (Mackenzie1999) state-based and continuous classes respectively. Behavior arbitration schemes (Pattie Maes 1991) and (Toby Tyrrell 1991) emphasized the testing of hypotheses of behavior rather than solving real-life tasks. Konolige, et al (Kurt Konolige 1992) used fuzzy control in conjunction with modeling and planning techniques to provide reactive guidance of their robot. The shortcomings of the above approaches are as follows: (i) When multiple obstacles present in the environment with equal distances as perceived from multiple sensors of robot, then the corresponding multiple obstacles are treated as a whole and the robot deviates from encountered obstacles widely, avoids obstacles and reaches the target. As a result of the wide deviation, the robot takes longer time and path to reach the target position. (ii)Behavior rule conflicts when multiple obstacles appear in the environment with equal distances from robot.The robot navigation in the optimal path, time and rule selection are more important and becoming critical factors whenever the mobile robots are engaged to search the lives in the event of natural disaster like earthquake etc. The Alpha Level Fuzzy Logic System (ALFLS) is established to resolve the above shortcomings. In this methodology, environmental perceptual field is well defined by a set of control parameters through alpha level intervals of fuzzy sets and their fuzzy membership values respectively. In the proposed method the alpha level threshold maximizes the truth for a particular behavior rule that needs to be fired at a time. The formulation to estimate the defuzzified output of conflicting situation is established theoretically and investigated experimentally and are given in the following sections. |
| first_indexed | 2025-11-14T08:17:40Z |
| format | Conference Paper |
| id | curtin-20.500.11937-30154 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T08:17:40Z |
| publishDate | 2006 |
| publisher | Curran Associates |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-301542017-02-28T01:51:38Z Mobile robot navigation using alpha level fuzzy logic system: Theoretical and experimental investigations Parasuraman, S. Ganapathy, V. Shirinzadeh, B. Zhong, Yongmin Billingsley, John, ed. Numerous behavior rule selection mechanisms have been studied and examples of such mechanisms are discussed. Saffiotti (Saffiotti 2000) suggests dividing action selection mechanisms into two groups that he calls arbitration and command fusion which correspond to Mackenzie's (Mackenzie1999) state-based and continuous classes respectively. Behavior arbitration schemes (Pattie Maes 1991) and (Toby Tyrrell 1991) emphasized the testing of hypotheses of behavior rather than solving real-life tasks. Konolige, et al (Kurt Konolige 1992) used fuzzy control in conjunction with modeling and planning techniques to provide reactive guidance of their robot. The shortcomings of the above approaches are as follows: (i) When multiple obstacles present in the environment with equal distances as perceived from multiple sensors of robot, then the corresponding multiple obstacles are treated as a whole and the robot deviates from encountered obstacles widely, avoids obstacles and reaches the target. As a result of the wide deviation, the robot takes longer time and path to reach the target position. (ii)Behavior rule conflicts when multiple obstacles appear in the environment with equal distances from robot.The robot navigation in the optimal path, time and rule selection are more important and becoming critical factors whenever the mobile robots are engaged to search the lives in the event of natural disaster like earthquake etc. The Alpha Level Fuzzy Logic System (ALFLS) is established to resolve the above shortcomings. In this methodology, environmental perceptual field is well defined by a set of control parameters through alpha level intervals of fuzzy sets and their fuzzy membership values respectively. In the proposed method the alpha level threshold maximizes the truth for a particular behavior rule that needs to be fired at a time. The formulation to estimate the defuzzified output of conflicting situation is established theoretically and investigated experimentally and are given in the following sections. 2006 Conference Paper http://hdl.handle.net/20.500.11937/30154 Curran Associates restricted |
| spellingShingle | Parasuraman, S. Ganapathy, V. Shirinzadeh, B. Zhong, Yongmin Mobile robot navigation using alpha level fuzzy logic system: Theoretical and experimental investigations |
| title | Mobile robot navigation using alpha level fuzzy logic system: Theoretical and experimental investigations |
| title_full | Mobile robot navigation using alpha level fuzzy logic system: Theoretical and experimental investigations |
| title_fullStr | Mobile robot navigation using alpha level fuzzy logic system: Theoretical and experimental investigations |
| title_full_unstemmed | Mobile robot navigation using alpha level fuzzy logic system: Theoretical and experimental investigations |
| title_short | Mobile robot navigation using alpha level fuzzy logic system: Theoretical and experimental investigations |
| title_sort | mobile robot navigation using alpha level fuzzy logic system: theoretical and experimental investigations |
| url | http://hdl.handle.net/20.500.11937/30154 |