Fuzzy Logic Control for Indoor Navigation of Mobile Robots
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arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866912014299824128 |
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| author | Kumar, Akshay Sahasrabudhe, Ashwin Nirgude, Sanjuksha |
| author_facet | Kumar, Akshay Sahasrabudhe, Ashwin Nirgude, Sanjuksha |
| contents | Autonomous mobile robots have many applications in indoor unstructured environment, wherein optimal movement of the robot is needed. The robot therefore needs to navigate in unknown and dynamic environments. This paper presents an implementation of fuzzy logic controller for navigation of mobile robot in an unknown dynamically cluttered environment. Fuzzy logic controller is used here as it is capable of making inferences even under uncertainties. It helps in rule generation and decision making process in order to reach the goal position under various situations. Sensor readings from the robot and the desired direction of motion are inputs to the fuzz logic controllers and the acceleration of the respective wheels are the output of the controller. Hence, the mobile robot avoids obstacles and reaches the goal position. Keywords: Fuzzy Logic Controller, Membership Functions, Takagi-Sugeno-Kang FIS, Centroid Defuzzification |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_02437 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Fuzzy Logic Control for Indoor Navigation of Mobile Robots Kumar, Akshay Sahasrabudhe, Ashwin Nirgude, Sanjuksha Robotics Autonomous mobile robots have many applications in indoor unstructured environment, wherein optimal movement of the robot is needed. The robot therefore needs to navigate in unknown and dynamic environments. This paper presents an implementation of fuzzy logic controller for navigation of mobile robot in an unknown dynamically cluttered environment. Fuzzy logic controller is used here as it is capable of making inferences even under uncertainties. It helps in rule generation and decision making process in order to reach the goal position under various situations. Sensor readings from the robot and the desired direction of motion are inputs to the fuzz logic controllers and the acceleration of the respective wheels are the output of the controller. Hence, the mobile robot avoids obstacles and reaches the goal position. Keywords: Fuzzy Logic Controller, Membership Functions, Takagi-Sugeno-Kang FIS, Centroid Defuzzification |
| title | Fuzzy Logic Control for Indoor Navigation of Mobile Robots |
| topic | Robotics |
| url | https://arxiv.org/abs/2409.02437 |