Sensor fusion for mobile robot navigation: fuzzy associative memory

Subramaniam Parasuraman

    Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

    5 Citations (Scopus)

    Abstract

    The mobile robot navigation with complex environment needs more input space to match the environmental data into robot outputs in order to perform a realistic task. At the same time, the number of rules at the rule base needs to be optimized to reduce the computing time and to provide the possibilities for real time operation. In this paper, a sensor fusion technique is proposed to enhance the navigation rules using a Modified Fuzzy Associative Memory. In the proposed method, the rule base uses fuzzy compositional rule of inference and fuzzy associativity. This technique provides good flexibility to use multiple input space and reduction of rule base for robot navigation. The behavior rules obtained from Modified Fuzzy Associative Memory model are tested using simulation and real world experiments, and the results are discussed in the paper and compared with the existing methods.
    Original languageEnglish
    Title of host publicationProceedings of the 2nd International Symposium on Robotics and Intelligent Sensors 2012 (IRIS 2012)
    EditorsHanafiah Yussof, Hayder Al-Assadi
    Place of PublicationNetherlands
    PublisherElsevier
    Pages251 - 256
    Number of pages6
    ISBN (Electronic)1877-7058
    DOIs
    Publication statusPublished - 2012
    EventInternational Symposium on Robotics and Intelligent Sensors (IRIS 2012) - Hilton Hotel, Kuching, Sarawak, Malaysia
    Duration: 4 Sep 20126 Sep 2012
    http://www.wikicfp.com/cfp/servlet/event.showcfp?eventid=21195&copyowner..

    Conference

    ConferenceInternational Symposium on Robotics and Intelligent Sensors (IRIS 2012)
    Abbreviated titleIRIS 2012
    CountryMalaysia
    CityKuching, Sarawak
    Period4/09/126/09/12
    Other2012 International Symposium on Robotics and Intelligent Sensors

    September 4-6, 2012, Kuching, Sarawak, Malaysia

    Theme:

    "SMART SENSORS, SMART ROBOTS"

    Venue: Hilton Hotel, Kuching, Sarawak

    Welcome to the 2nd International Symposium on Robotics and Intelligent Sensors 2012 (IRIS2012). The event is organized by Universiti Teknologi MARA (UiTM), Malaysia, the Malaysian Robotics and Automation Interest Group (MYRAig), and Nagoya University, Japan. IRIS2012 is intended to provide technical forum and discussion related with robotics and sensors. The symposium is aimed to bring together researchers, academicians, scientists, students, engineers and practitioners to participate and present their latest findings, ideas, developments and applications related to the various aspects of robotics and sensors. IRIS2012 will features interactive Technical Sessions, Special Sessions, Workshop and Exhibition. The programs include keynote addresses by eminent scientists as well as presentation by delegates from industries. IRIS2012 proceedings is indexed in IEEE Xplorer (in progress) and extended version of selected best papers will be consider for publication in selected journals. Papers presented in Special Session will be publish in both proceedings and journal.
    Internet address

    Cite this

    Parasuraman, S. (2012). Sensor fusion for mobile robot navigation: fuzzy associative memory. In H. Yussof, & H. Al-Assadi (Eds.), Proceedings of the 2nd International Symposium on Robotics and Intelligent Sensors 2012 (IRIS 2012) (pp. 251 - 256). Netherlands: Elsevier. https://doi.org/10.1016/j.proeng.2012.07.170
    Parasuraman, Subramaniam. / Sensor fusion for mobile robot navigation: fuzzy associative memory. Proceedings of the 2nd International Symposium on Robotics and Intelligent Sensors 2012 (IRIS 2012). editor / Hanafiah Yussof ; Hayder Al-Assadi. Netherlands : Elsevier, 2012. pp. 251 - 256
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    title = "Sensor fusion for mobile robot navigation: fuzzy associative memory",
    abstract = "The mobile robot navigation with complex environment needs more input space to match the environmental data into robot outputs in order to perform a realistic task. At the same time, the number of rules at the rule base needs to be optimized to reduce the computing time and to provide the possibilities for real time operation. In this paper, a sensor fusion technique is proposed to enhance the navigation rules using a Modified Fuzzy Associative Memory. In the proposed method, the rule base uses fuzzy compositional rule of inference and fuzzy associativity. This technique provides good flexibility to use multiple input space and reduction of rule base for robot navigation. The behavior rules obtained from Modified Fuzzy Associative Memory model are tested using simulation and real world experiments, and the results are discussed in the paper and compared with the existing methods.",
    author = "Subramaniam Parasuraman",
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    language = "English",
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    Parasuraman, S 2012, Sensor fusion for mobile robot navigation: fuzzy associative memory. in H Yussof & H Al-Assadi (eds), Proceedings of the 2nd International Symposium on Robotics and Intelligent Sensors 2012 (IRIS 2012). Elsevier, Netherlands, pp. 251 - 256, International Symposium on Robotics and Intelligent Sensors (IRIS 2012), Kuching, Sarawak, Malaysia, 4/09/12. https://doi.org/10.1016/j.proeng.2012.07.170

    Sensor fusion for mobile robot navigation: fuzzy associative memory. / Parasuraman, Subramaniam.

    Proceedings of the 2nd International Symposium on Robotics and Intelligent Sensors 2012 (IRIS 2012). ed. / Hanafiah Yussof; Hayder Al-Assadi. Netherlands : Elsevier, 2012. p. 251 - 256.

    Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

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    AB - The mobile robot navigation with complex environment needs more input space to match the environmental data into robot outputs in order to perform a realistic task. At the same time, the number of rules at the rule base needs to be optimized to reduce the computing time and to provide the possibilities for real time operation. In this paper, a sensor fusion technique is proposed to enhance the navigation rules using a Modified Fuzzy Associative Memory. In the proposed method, the rule base uses fuzzy compositional rule of inference and fuzzy associativity. This technique provides good flexibility to use multiple input space and reduction of rule base for robot navigation. The behavior rules obtained from Modified Fuzzy Associative Memory model are tested using simulation and real world experiments, and the results are discussed in the paper and compared with the existing methods.

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    Parasuraman S. Sensor fusion for mobile robot navigation: fuzzy associative memory. In Yussof H, Al-Assadi H, editors, Proceedings of the 2nd International Symposium on Robotics and Intelligent Sensors 2012 (IRIS 2012). Netherlands: Elsevier. 2012. p. 251 - 256 https://doi.org/10.1016/j.proeng.2012.07.170