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Ȩ Ȩ > ¿¬±¸¹®Çå > ±¹³» ³í¹®Áö > Çѱ¹Á¤º¸°úÇÐȸ ³í¹®Áö > Á¤º¸°úÇÐȸ³í¹®Áö (Journal of KIISE)

Á¤º¸°úÇÐȸ³í¹®Áö (Journal of KIISE)

Current Result Document :

ÇѱÛÁ¦¸ñ(Korean Title) Áö´ÉÇü ¼­ºñ½º ·Îº¿À» À§ÇÑ ¿ÂÅç·ÎÁö ±â¹ÝÀÇ µ¿Àû »óȲ °ü¸® ¹× ½Ã-°ø°£ Ãß·Ð
¿µ¹®Á¦¸ñ(English Title) Ontology-Based Dynamic Context Management and Spatio-Temporal Reasoning for Intelligent Service Robots
ÀúÀÚ(Author) ±èÁ¾ÈÆ   À̼®ÁØ   ±èµ¿ÇÏ   ±èÀÎö   Jonghoon Kim   Seokjun Lee   Dongha Kim   Incheol Kim  
¿ø¹®¼ö·Ïó(Citation) VOL 43 NO. 12 PP. 1365 ~ 1375 (2016. 12)
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(Korean Abstract)
ÀÏ»ó»ýÈ° ȯ°æ ¼Ó¿¡¼­ ÀÚÀ²ÀûÀ¸·Î µ¿ÀÛÇÏ´Â ¼­ºñ½º ·Îº¿¿¡°Ô °¡Àå ÇʼöÀûÀÎ ´É·Â Áß Çϳª°¡ µ¿ÀûÀ¸·Î º¯È­ÇÏ´Â ÁÖº¯ ȯ°æ¿¡ ´ëÇÑ ¿Ã¹Ù¸¥ »óȲ Àνİú ÀÌÇØ ´É·ÂÀÌ´Ù. ´Ù¾çÇÑ ¼¾¼­ µ¥ÀÌÅÍ ½ºÆ®¸²µé·ÎºÎÅÍ ½Å¼ÓÈ÷ ÀÇ»ç °áÁ¤¿¡ ÇÊ¿äÇÑ °í¼öÁØÀÇ »óȲ Áö½ÄÀ» »ý¼ºÇس»±â À§Çؼ­´Â, ¸ÖƼ ¸ð´Þ ¼¾¼­ µ¥ÀÌÅÍÀÇ À¶ÇÕ, ºÒÈ®½Ç¼º ó¸®, ±âÈ£Áö½ÄÀÇ ½Çüȭ, ½Ã°£ ÀÇÁ¸¼º°ú °¡º¯¼º ó¸®, ½Ç½Ã°£¼ºÀ» ¸¸Á·ÇÒ ¼ö ÀÖ´Â ½Ã-°ø°£ Ãß·Ð µî ¸¹Àº ¹®Á¦µéÀÌ ÇØ°áµÇ¾î¾ß ÇÑ´Ù. ÀÌ¿Í °°Àº ¹®Á¦µéÀ» °í·ÁÇÏ¿©, º» ³í¹®¿¡¼­´Â Áö´ÉÇü ¼­ºñ½º ·Îº¿À» À§ÇÑ È¿°úÀûÀÎ µ¿Àû »óȲ°ü¸® ¹× ½Ã-°ø°£ Ãß·Ð ¹æ¹ýÀ» Á¦½ÃÇÑ´Ù. º» ³í¹®¿¡¼­´Â »óȲ Áö½Ä °ü¸®¿Í Ãß·ÐÀÇ È¿À²¼ºÀ» ±Ø´ëÈ­ Çϱâ À§ÇØ, Àú ¼öÁØÀÇ »óȲ Áö½ÄÀº ¼¾¼­ ¹× ÀÎ½Ä µ¥ÀÌÅÍ°¡ ÀÔ·ÂµÉ ¶§ ¸¶´Ù ½Ç½Ã°£ÀûÀ¸·Î »ý¼ºµÇÁö¸¸, ¹Ý¸é¿¡ °í¼öÁØÀÇ »óȲ Áö½ÄÀº ÀÇ»ç °áÁ¤ ¸ðµâ¿¡¼­ ¿ä±¸°¡ ÀÖÀ» ¶§ ¸¸ ÈÄÇâ ½Ã-°ø°£ Ãß·ÐÀ» ÅëÇØ À¯µµµÇµµ·Ï ¾Ë°í¸®ÁòÀ» ¼³°èÇÏ¿´´Ù. Kinect ½Ã°¢ ¼¾¼­ ±â¹ÝÀÇ Turtlebot¸¦ ÀÌ¿ëÇÑ ½ÇÇèÀ» ÅëÇØ, Á¦¾ÈÇÑ ¹æ¹ý¿¡ ±âÃÊÇÑ µ¿Àû »óȲ °ü¸® ¹× Ãß·Ð ½Ã½ºÅÛÀÇ ³ôÀº È¿À²¼ºÀ» È®ÀÎÇÒ ¼ö ÀÖ¾ú´Ù.
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(English Abstract)
One of the most important capabilities for autonomous service robots working in living environments is to recognize and understand the correct context in dynamically changing environment. To generate high-level context knowledge for decision-making from multiple sensory data streams, many technical problems such as multi-modal sensory data fusion, uncertainty handling, symbolic knowledge grounding, time dependency, dynamics, and time-constrained spatio-temporal reasoning should be solved. Considering these problems, this paper proposes an effective dynamic context management and spatio-temporal reasoning method for intelligent service robots. In order to guarantee efficient context management and reasoning, our algorithm was designed to generate low-level context knowledge reactively for every input sensory or perception data, while postponing high-level context knowledge generation until it was demanded by the decision-making module. When high-level context knowledge is demanded, it is derived through backward spatio-temporal reasoning. In experiments with Turtlebot using Kinect visual sensor, the dynamic context management and spatio-temporal reasoning system based on the proposed method showed high performance.
Å°¿öµå(Keyword) Áö´ÉÇü¼­ºñ½º·Îº¿   »óȲ°ü¸®   ½Ã-°ø°£Ã߷Р  ¿ÂÅç·ÎÁö   °è»êÇü¼­¼úÀÚ   intelligent service robot   context management   spatio-temporal reasoning   ontology   computable predicate  
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