Adaptive behavior of evolutionary neurocontroller for obstacle avoidance mobile robot
This research aims to analyze the adaptive behavior of an artificial neural network-based controller (neurocontroller) for an obstacle avoidance wheeled mobile robot. The neurocontroller of interest is the best of an ecosystem of neurocontrollers that evolved according to the genetic algorithm. The...
| Main Authors: | , , |
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| Format: | Journal Article |
| Language: | English |
| Published: |
2015
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| Online Access: | https://hdl.handle.net/10356/106630 http://hdl.handle.net/10220/25058 http://www.internetworkingindonesia.org/Issues/Vol5-No1-B-2013/iij-vol5-no1-b-2013.html |
| _version_ | 1811690269584654336 |
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| author | Gani, Aloysius Aldo Tan, Sofyan Meiliayana |
| author2 | School of Computer Engineering |
| author_facet | School of Computer Engineering Gani, Aloysius Aldo Tan, Sofyan Meiliayana |
| author_sort | Gani, Aloysius Aldo |
| collection | NTU |
| description | This research aims to analyze the adaptive behavior of an artificial neural network-based controller (neurocontroller) for an obstacle avoidance wheeled mobile robot. The neurocontroller of interest is the best of an ecosystem of neurocontrollers that evolved according to the genetic algorithm. The chromosome of each individual neurocontroller is simply the binary weights of the connections, and the fitness function is a simple rule for obstacle avoidance behavior. To limit the hardware requirements, the neurocontroller’s evolution is simulated in a computer, and the best neurocontroller behavior is analyzed in the simulation and in an actual mobile robot. Albeit a simple chromosome, the resulting best neurocontroller showed an obstacle avoidance behavior in both simulation and in the actual mobile robot, regardless of the positions of obstacles in the environment. The analysis of the chromosome after evolution also found that not all of the sensors are actually needed for the obstacle avoidance behavior. |
| first_indexed | 2024-10-01T06:01:19Z |
| format | Journal Article |
| id | ntu-10356/106630 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T06:01:19Z |
| publishDate | 2015 |
| record_format | dspace |
| spelling | ntu-10356/1066302020-05-28T07:17:16Z Adaptive behavior of evolutionary neurocontroller for obstacle avoidance mobile robot Gani, Aloysius Aldo Tan, Sofyan Meiliayana School of Computer Engineering DRNTU::Engineering::Computer science and engineering::Software This research aims to analyze the adaptive behavior of an artificial neural network-based controller (neurocontroller) for an obstacle avoidance wheeled mobile robot. The neurocontroller of interest is the best of an ecosystem of neurocontrollers that evolved according to the genetic algorithm. The chromosome of each individual neurocontroller is simply the binary weights of the connections, and the fitness function is a simple rule for obstacle avoidance behavior. To limit the hardware requirements, the neurocontroller’s evolution is simulated in a computer, and the best neurocontroller behavior is analyzed in the simulation and in an actual mobile robot. Albeit a simple chromosome, the resulting best neurocontroller showed an obstacle avoidance behavior in both simulation and in the actual mobile robot, regardless of the positions of obstacles in the environment. The analysis of the chromosome after evolution also found that not all of the sensors are actually needed for the obstacle avoidance behavior. Published version 2015-02-13T07:03:03Z 2019-12-06T22:15:13Z 2015-02-13T07:03:03Z 2019-12-06T22:15:13Z 2013 2013 Journal Article Gani, A. A., Tan, S., & Meiliayana. (2013). Adaptive behavior of evolutionary neurocontroller for obstacle avoidance mobile robot. Internetworking Indonesia Journal,5(1), 31-36. 1942-9703 https://hdl.handle.net/10356/106630 http://hdl.handle.net/10220/25058 http://www.internetworkingindonesia.org/Issues/Vol5-No1-B-2013/iij-vol5-no1-b-2013.html en Internetworking Indonesia journal © 2013 Internetworking Indonesia Journal. This paper was published in Internetworking Indonesia Journal and is made available as an electronic reprint (preprint) with permission of Internetworking Indonesia Journal. The paper can be found at the following URL: [http://www.internetworkingindonesia.org/Issues/Vol5-No1-B-2013/iij-vol5-no1-b-2013.html]. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper is prohibited and is subject to penalties under law. application/pdf |
| spellingShingle | DRNTU::Engineering::Computer science and engineering::Software Gani, Aloysius Aldo Tan, Sofyan Meiliayana Adaptive behavior of evolutionary neurocontroller for obstacle avoidance mobile robot |
| title | Adaptive behavior of evolutionary neurocontroller for obstacle avoidance mobile robot |
| title_full | Adaptive behavior of evolutionary neurocontroller for obstacle avoidance mobile robot |
| title_fullStr | Adaptive behavior of evolutionary neurocontroller for obstacle avoidance mobile robot |
| title_full_unstemmed | Adaptive behavior of evolutionary neurocontroller for obstacle avoidance mobile robot |
| title_short | Adaptive behavior of evolutionary neurocontroller for obstacle avoidance mobile robot |
| title_sort | adaptive behavior of evolutionary neurocontroller for obstacle avoidance mobile robot |
| topic | DRNTU::Engineering::Computer science and engineering::Software |
| url | https://hdl.handle.net/10356/106630 http://hdl.handle.net/10220/25058 http://www.internetworkingindonesia.org/Issues/Vol5-No1-B-2013/iij-vol5-no1-b-2013.html |
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