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A Cognitive Robotic System for a Human-Following Robot
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dc.contributor.author Dang, Van Chien -
dc.contributor.author Ahn, Heungju -
dc.contributor.author Seo, Hyeon Cheol -
dc.contributor.author Lee, Sang Cheol -
dc.date.accessioned 2023-12-26T19:12:39Z -
dc.date.available 2023-12-26T19:12:39Z -
dc.date.created 2021-01-14 -
dc.date.issued 2020-11-16 -
dc.identifier.isbn 9781643681351 -
dc.identifier.issn 0922-6389 -
dc.identifier.uri http://hdl.handle.net/20.500.11750/46960 -
dc.description.abstract In this paper we propose a cognitive robotic system that utilizes computational psychology (the Soar cognitive architecture) and an obstacle avoidance method (modified dynamic window approach) in ROS (Robot Operating System) platform for controlling a mobile robot. This system is applied to perform a task of human-following, aiming to help the robot navigate itself to the target person avoiding collision. A cognitive agent based on Soar cognitive architecture is created to reason its current situation and make decisions on movement direction such as go-straight, turn-left or turn-right, whereas the dynamic window approach is modified to avoid collision by computing appropriate velocities for driving the robot motors. To the end, a part of implementation is presented to describes how the system works. © 2020 The authors and IOS Press. -
dc.language English -
dc.publisher IOS Press -
dc.title A Cognitive Robotic System for a Human-Following Robot -
dc.type Conference Paper -
dc.identifier.doi 10.3233/faia200737 -
dc.identifier.scopusid 2-s2.0-85101508761 -
dc.identifier.bibliographicCitation Dang, Van Chien. (2020-11-16). A Cognitive Robotic System for a Human-Following Robot. 6th International Conference on Fuzzy Systems and Data Mining(FSDM 2020), 601–607. doi: 10.3233/faia200737 -
dc.identifier.url https://opensz.oss-cn-beijing.aliyuncs.com/FSDM2020/file/FSDM2020-Conference%20Program.pdf -
dc.citation.conferencePlace CC -
dc.citation.conferencePlace Xiamen -
dc.citation.endPage 607 -
dc.citation.startPage 601 -
dc.citation.title 6th International Conference on Fuzzy Systems and Data Mining(FSDM 2020) -
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안흥주
Ahn, Heungju안흥주

Department of Liberal Arts and Sciences

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