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Ȩ Ȩ > ¿¬±¸¹®Çå > ±¹³» ³í¹®Áö > Çѱ¹Á¤º¸Ã³¸®ÇÐȸ ³í¹®Áö > Á¤º¸Ã³¸®ÇÐȸ ³í¹®Áö ¼ÒÇÁÆ®¿þ¾î ¹× µ¥ÀÌÅÍ °øÇÐ

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Current Result Document : 8 / 91 ÀÌÀü°Ç ÀÌÀü°Ç   ´ÙÀ½°Ç ´ÙÀ½°Ç

ÇѱÛÁ¦¸ñ(Korean Title) º®¸é À̵¿·Îº¿ÀÇ ÀÚµ¿ ±Õ¿­°ËÃâ¿¡ ÀûÇÕÇÑ ±â°èÇнÀ ¾Ë°í¸®Áò¿¡ °üÇÑ ¿¬±¸
¿µ¹®Á¦¸ñ(English Title) A Study on Machine Learning Algorithm Suitable for Automatic Crack Detection in Wall-Climbing Robot
ÀúÀÚ(Author) ¹ÚÀç¹Î   ±èÇö¼·   ½Åµ¿È£   ¹Ú¸í¼÷   ±è»óÈÆ   Jae-Min Park   Hyun-Seop Kim   Dong-Ho Shin   Myeong-Suk Park   Sang-Hoon Kim  
¿ø¹®¼ö·Ïó(Citation) VOL 08 NO. 11 PP. 0449 ~ 0456 (2019. 11)
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(Korean Abstract)
º» ³í¹®Àº Áø°øÀ» ÀÌ¿ëÇÑ ÈíÂø¹æ½Ä°ú ¹ÙÄûÇü À̵¿¹æ½ÄÀ» »ç¿ëÇÏ´Â º®¸é À̵¿·Îº¿ ±¸¼º°ú ÀÌ·¯ÇÑ ÀÓº£µðµå ȯ°æ¿¡ ÀûÇÕÇÏ°í ±â°èÇнÀ¿¡ ±â¹ÝÇÑ º®¸é ±Õ¿­ ÀÚµ¿ °ËÃâ ¾Ë°í¸®ÁòÀÇ ¼º´É ºñ±³¿¡ °üÇÑ ¿¬±¸ÀÌ´Ù. ÀÓº£µðµå ½Ã½ºÅÛ È¯°æ¿¡¼­ °´Ã¼ ÇнÀÀ» À§ÇØ YOLO µî ÃÖ±Ù¿¡ ½ÃµµµÈ ÇнÀ ¹æ¹ýµéÀ» Àû¿ëÇÏ¿© ¼º´ÉÀ» ºñ±³, °ËÅäÇÏ¿´À¸¸ç ±âÁ¸ÀÇ ¿¡Áö °ËÃâ ¾Ë°í¸®Áòµé°úµµ ¼º´ÉÀ» ºñ±³ÇÏ¿´´Ù. °á±¹, º» ¿¬±¸¿¡¼­´Â ±Õ¿­°ËÃâÀ» ÀßÇϸç ÀÓº£µðµå ȯ°æ¿¡µµ ÀûÇÕÇÑ ÃÖÀûÀÇ ±â°èÇнÀ¹æ¹ýÀ» ¼±ÅÃÇÏ°í ±âÁ¸ ¹æ¹ý°ú ¼º´ÉÀ» ºñ±³ÇÏ¿© ¿ì¼ö¼ºÀ» Á¦½ÃÇÏ¿´´Ù. ¶ÇÇÑ, °ËÃâµÈ ±Õ¿­¿µ»óÀ» ÀúÀåÇÏ°í À§Ä¡ Á¤º¸¸¦ ÃßÁ¤ÇÏ¿© ±Õ¿­¿¡ ´ëÇÑ Á¤º¸¸¦ °ü¸®ÀÚ ±â±â·Î Àü¼ÛÇÏ´Â Áö´ÉÀûÀÎ ¹®Á¦ÇØ°á ±â´ÉÀ» ±¸ÃàÇÏ¿´´Ù.
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(English Abstract)
This paper is a study on the construction of a wall-climbing mobile robot using vacuum suction and wheel-type movement, and a comparison of the performance of an automatic wall crack detection algorithm based on machine learning that is suitable for such an embedded environment. In the embedded system environment, we compared performance by applying recently developed learning methods such as YOLO for object learning, and compared performance with existing edge detection algorithms. Finally, in this study, we selected the optimal machine learning method suitable for the embedded environment and good for extracting the crack features, and compared performance with the existing methods and presented its superiority. In addition, intelligent problem – solving function that transmits the image and location information of the detected crack to the manager device is constructed
Å°¿öµå(Keyword) º®¸é À̵¿·Îº¿   ±ÕÀÏ°ËÃâ ¾Ë°í¸®Áò   ±â°èÇнÀ   À§Ä¡ÃßÁ¤   Wall-Climbing Robot   Crack Detection Algorithms   Machine Learning   Localization  
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