A novel approach to motion modeling using fuzzy cognitive map and artificial potential fields
Artificial potential field (APF) is well established for reactive navigation of robots. Initially, this paper describes a fast and robust fuzzy-APF on an ActivMedia AmigoBot platform. Obstacle-related information is fuzzified just by sensory fusion which results in shorter runtime. The membership fu...
| Main Authors: | , , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
IEEE
2010
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| Online Access: | http://psasir.upm.edu.my/id/eprint/68309/ http://psasir.upm.edu.my/id/eprint/68309/1/A%20novel%20approach%20to%20motion%20modeling%20using%20fuzzy%20cognitive%20map%20and%20artificial%20potential%20fields.pdf |
| _version_ | 1848856090607878144 |
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| author | Motlagh, Omid Reza Esmaeili Tang, Sai Hong Ramli, Abdul Rahman Ismail, Napsiah Nakhaeinia, Danial |
| author_facet | Motlagh, Omid Reza Esmaeili Tang, Sai Hong Ramli, Abdul Rahman Ismail, Napsiah Nakhaeinia, Danial |
| author_sort | Motlagh, Omid Reza Esmaeili |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | Artificial potential field (APF) is well established for reactive navigation of robots. Initially, this paper describes a fast and robust fuzzy-APF on an ActivMedia AmigoBot platform. Obstacle-related information is fuzzified just by sensory fusion which results in shorter runtime. The membership functions of obstacles' range and direction have been also merged into one function for smaller block of rules. The fuzzy-APF is tested and verified virtually with non-concave obstacles. Main contribution of this article is a new approach to motion modeling. The goal is to discover decision making behaviors of the robot in wayfinding. A novel decision modeling technique is developed based on capabilities of the fuzzy cognitive map (FCM) and supervised learning using the genetic algorithm (GA). Decision productions for moving from one sub-space to another are modeled in form of decision matrices. The robot trajectory under supply of such decision matrices has likelihood of nearly 90% with its trajectory under the APF. Replication of robot motion is therefore achieved by modeling its decision behaviors in form of tangible matrices. |
| first_indexed | 2025-11-15T11:36:08Z |
| format | Conference or Workshop Item |
| id | upm-68309 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T11:36:08Z |
| publishDate | 2010 |
| publisher | IEEE |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-683092019-05-10T08:30:58Z http://psasir.upm.edu.my/id/eprint/68309/ A novel approach to motion modeling using fuzzy cognitive map and artificial potential fields Motlagh, Omid Reza Esmaeili Tang, Sai Hong Ramli, Abdul Rahman Ismail, Napsiah Nakhaeinia, Danial Artificial potential field (APF) is well established for reactive navigation of robots. Initially, this paper describes a fast and robust fuzzy-APF on an ActivMedia AmigoBot platform. Obstacle-related information is fuzzified just by sensory fusion which results in shorter runtime. The membership functions of obstacles' range and direction have been also merged into one function for smaller block of rules. The fuzzy-APF is tested and verified virtually with non-concave obstacles. Main contribution of this article is a new approach to motion modeling. The goal is to discover decision making behaviors of the robot in wayfinding. A novel decision modeling technique is developed based on capabilities of the fuzzy cognitive map (FCM) and supervised learning using the genetic algorithm (GA). Decision productions for moving from one sub-space to another are modeled in form of decision matrices. The robot trajectory under supply of such decision matrices has likelihood of nearly 90% with its trajectory under the APF. Replication of robot motion is therefore achieved by modeling its decision behaviors in form of tangible matrices. IEEE 2010 Conference or Workshop Item PeerReviewed text en http://psasir.upm.edu.my/id/eprint/68309/1/A%20novel%20approach%20to%20motion%20modeling%20using%20fuzzy%20cognitive%20map%20and%20artificial%20potential%20fields.pdf Motlagh, Omid Reza Esmaeili and Tang, Sai Hong and Ramli, Abdul Rahman and Ismail, Napsiah and Nakhaeinia, Danial (2010) A novel approach to motion modeling using fuzzy cognitive map and artificial potential fields. In: 11th International Conference on Control, Automation, Robotics and Vision (ICARCV 2010), 7-10 Dec. 2010, Singapore. (pp. 1963-1967). 10.1109/ICARCV.2010.5707297 |
| spellingShingle | Motlagh, Omid Reza Esmaeili Tang, Sai Hong Ramli, Abdul Rahman Ismail, Napsiah Nakhaeinia, Danial A novel approach to motion modeling using fuzzy cognitive map and artificial potential fields |
| title | A novel approach to motion modeling using fuzzy cognitive map and artificial potential fields |
| title_full | A novel approach to motion modeling using fuzzy cognitive map and artificial potential fields |
| title_fullStr | A novel approach to motion modeling using fuzzy cognitive map and artificial potential fields |
| title_full_unstemmed | A novel approach to motion modeling using fuzzy cognitive map and artificial potential fields |
| title_short | A novel approach to motion modeling using fuzzy cognitive map and artificial potential fields |
| title_sort | novel approach to motion modeling using fuzzy cognitive map and artificial potential fields |
| url | http://psasir.upm.edu.my/id/eprint/68309/ http://psasir.upm.edu.my/id/eprint/68309/ http://psasir.upm.edu.my/id/eprint/68309/1/A%20novel%20approach%20to%20motion%20modeling%20using%20fuzzy%20cognitive%20map%20and%20artificial%20potential%20fields.pdf |