\n\n\n\n
- Deep-Learning \uc744 \ud65c\uc6a9\ud55c \ub85c\ubd07\uc758 Interaction Force \uc608\uce21<\/strong>(\uc0bc\uc131\uc804\uc790 \ubbf8\ub798\uc721\uc131\uc13c\ud1302017-2020)
(Inferring Interaction Force of Robot from only Visual Information without Force\/Torque Sensor)<\/strong><\/li><\/ul>\n\n\n\n![\"Forceestimation\"](\"http:\/\/irobot.dgu.edu\/wordpress\/wp-content\/uploads\/2016\/06\/Forceestimation-1-200x300.jpg\")
<\/figure>\n\n\n\n![\"foE2\"](\"http:\/\/irobot.dgu.edu\/wordpress\/wp-content\/uploads\/2016\/06\/foE2-1-1024x431.png\")
<\/figure>\n\n\n\n– \uc601\uc0c1 \ubc0f \ub85c\ubd07 \uc6c0\uc9c1\uc784\uc5d0 \uae30\ubc18\ud55c \ud559\uc2b5\uc744 \ud1b5\ud574 \ub85c\ubd07\uacfc \ud658\uacbd\uacfc\uc758 Interaction force\ub97c \uc608\uce21\ud558\uace0 \uc774\ub97c \uae30\ubc18\uc73c\ub85c \ud55c \ub85c\ubd07 \uc6d0\uaca9\uc870\uc885 \ud585\ud2f1 \ud53c\ub4dc\ubc31
: \ub85c\ubd07\uc774 \ubb3c\uccb4\uc640 \uc0c1\ud638\uc791\uc6a9 \uc2dc \uc0dd\uc131\ub418\ub294 \uc0c1\ud638\uc791\uc6a9 \ud798 \uad00\ub828 DB \uc0dd\uc131
: \ub85c\ubd07 \uc6d0\uaca9 \uc81c\uc5b4 \ub610\ub294 \uc790\uc728 \uc6c0\uc9c1\uc784 \uc2dc \ud658\uacbd\uacfc\uc758 \uc0c1\ud638\uc791\uc6a9 \ud798\uc744 \uc601\uc0c1(RGB \ub610\ub294 RGB-D) \ubc0f \ub85c\ubd07\uc758 \uc6c0\uc9c1\uc784\uc815\ubcf4\uc640 \ubaa8\ud130\uc758 \uc804\ub958 \uc815\ubcf4\ub97c \uae30\ubc18\uc73c\ub85c \ubb3c\ub9ac\uc801 \uac10\uac01 \uc7ac\ud604 \uc608\uce21 \ubaa8\ub4c8 \uc5f0\uad6c
: \uc608\uce21\ub41c \ud798\uc744 \uc6d0\uaca9\uc81c\uc5b4\uc5d0 \ud65c\uc6a9\ud55c \ud585\ud2f1 \ud53c\ub4dc\ubc31 \uc2dc\uc2a4\ud15c<\/p>\n\n\n\n\u201cVision-Based Interaction Force Estimation of Robot without Tactile and Force_Torque Sensor\u201d, IEEE Industrial Informatics, Under review<\/em>
\u201cSequential Image-based Attention Network for Inferring Force Estimation without Haptic Sensor\u201d, IEEE Access, early access, <\/em>2019, DOI:10.1109\/ACCESS.2019.2947090<\/a>
\u201cAn Efficient Three-Dimensional Convolutional Neural Network for Inferring Physical Interaction Force from Video\u201d, Sensors<\/em>, 19(16), 3579, 2019, doi : 10.3390\/s19163579<\/a>
\u201cInteraction Force Estimation using Camera and Electrical Current without Force\/Torque Sensor\u201d. IEEE Sensors Journal, Vol 18, No. 21, pp 8863-8872, 2018, doi: 10.1109\/JSEN.2018.2868332<\/a>
\u201cInferring Interaction Force from Visual Information without Using Physical Force Sensors\u201d, Sensors<\/em>, 17(11), 2455, 2017, doi: 10.3390\/s17112455<\/a><\/p>\n\n\n\n
\n\n\n\n- \ub85c\ubd07 \uc6d0\uaca9\uc81c\uc5b4\uc2dc \ubb3c\ub9ac\uc801 \uc785\ub825\uac12\uc744 \ud65c\uc6a9\ud55c \uc2dc\uac04\uc9c0\uc5f0\uc5c6\ub294 \uc601\uc0c1 \uc0dd\uc131 \uae30\ubc95 \uac1c\ubc1c<\/strong>(\uacfc\ud559\uae30\uc220\ubd80-\uc911\uacac\uc5f0\uad6c, 2020~2023)<\/li><\/ul>\n\n\n\n
![\"\ucea1\ucc982\"](\"http:\/\/irobot.dgu.edu\/wordpress\/wp-content\/uploads\/2016\/06\/2.png\")
<\/figure><\/div>\n\n\n\n– \uc0ac\uc6a9\uc790\uac00 \ub85c\ubd07 \uc6d0\uaca9\uc870\uc885 \uc2dc \ub124\ud2b8\uc6cc\ud06c \ubc0f \ubb3c\ub9ac\uc801 \uac70\ub9ac\uc758 \ud55c\uacc4\ub97c \uadf9\ubcf5\ud558\uace0 \uc601\uc0c1\uc744 \uc804\ub2ec\ud558\uae30 \uc704\ud574, \uc6d0\uaca9\uc9c0\uc5d0\uc11c \uc0ac\uc6a9\ub418\ub294 \ud070 \uc774\ubbf8\uc9c0\uc758 \uc804\uc1a1 \ube48\ub3c4\uc218\ub97c \uc904\uc5ec \uc804\uc1a1\ud55c \uc9c0\uc5f0\ub41c \uc601\uc0c1\uc815\ubcf4, \uc9c0\uc5f0\ub418\uc11c \ubc1b\ub294 \ub85c\ubd07\uc758 \uc0c1\ud638\uc791\uc6a9 \ud798 \uc815\ubcf4 \ubc0f \uc6d0\uaca9 \uc870\uc791 \uc815\ubcf4\ub97c \uc870\uc885\uc790\uc758 \uc870\uc885\uc785\ub825\uac12\uacfc \uac19\uc774 \uc0ac\uc6a9\ud558\uc5ec\ub525\ub7ec\ub2dd \uae30\ubc95\uc744 \ud65c\uc6a9\ud55c \uc2e4\uc2dc\uac04 \uc601\uc0c1 \uc0dd\uc131 \ubc0f \uc0c1\ud638\uc791\uc6a9 \ud798 \uc0dd\uc131 \ubc29\ubc95\uc744 \uac1c\ubc1c\ud558\uace0 \uc774 \uc601\uc0c1 \ubc0f \ud798 \uc815\ubcf4\ub97c \uc0ac\uc6a9\uc790\uc5d0\uac8c \ud53c\ub4dc\ubc31 \ud558\uc5ec \uc6d0\uaca9\ub85c\ubd07 \uc81c\uc5b4\ud568<\/p>\n\n\n\n
\u201cContinuous Image Generation from Low-Update-Rate Images and Physical Sensors through a Conditional GAN for Robot Teleoperation\u201d, IEEE Transactions on Industrial Informatics, 2020, Accepted, DOI: <\/strong>10.1109\/TII.2020.2991764<\/a><\/p>\n\n\n\n
\n\n\n\n- \uace0\uc720\uc218\uc6a9\uc131 \uac10\uac01\uc758 \uce21\uc815 \ubc0f \uc0ac\uc6a9\uc790 \ud798\uc99d\uac15\uc744 \uc704\ud55c Exoskeleton \uac1c\ubc1c<\/strong><\/li><\/ul>\n\n\n\n
\n\n\n\n- EMG\/EEG \uc2e0\ud638\ub97c \ud65c\uc6a9\ud55c Interaction force \uc608\uce21<\/strong><\/li><\/ul>\n\n\n\n
\n\n\n\n- \ub525\ub7ec\ub2dd\uc744 \uc0ac\uc6a9\ud55c \uacf5\uacf5\uae30\uc220\uc758 \uae30\uc220\uc0ac\uc5c5\ud654 \uc5ec\ubd80 \ud310\ub2e8 \ubaa8\ub378 \uac1c\ubc1c<\/strong>(KISTI, 2020)<\/li><\/ul>\n\n\n\n
\n\n\n\nPAST<\/h3>\n\n\n\n
- \uc601\uc0c1 \uae30\ubc18\uc758 \uc785\ub825 \uac00\ub2a5\ud55c digital pen(\uad50\uc721\ubd80, 2018-2019)<\/li>
- \ucd09\uac01 \uc13c\uc11c\ub97c \ud65c\uc6a9\ud55c \uc6d0\uaca9 \uc218\uc220\ub85c\ubd07\/\uc6d0\uaca9 \uc190 \uc81c\uc5b4 (\uc0b0\uc5c5\ud1b5\uc0c1\uc790\uc6d0\ubd80, 2017-2020)<\/li>
- Proprioception(\uace0\uc720\uc218\uc6a9\uc131\uac10\uac01) \uce21\uc815\uc744 \uc704\ud55c \uc7a5\uce58 \uc124\uacc4 \ubc0f VR \ud65c\uc6a9 \uc2e4\ud5d8 (\ubcf4\uac74\ubcf5\uc9c0\ubd80,\uad6d\ub9bd\uc7ac\ud65c\uc6d0, 2017)<\/li>
- Visual-tactile sensory perception (\uad50\uc721\ubd80, 2016-2018)<\/li>
- 360\ub3c4 \uc601\uc0c1 \ucd2c\uc601\uc744 \uc704\ud55c \uc6d0\uaca9 \uc870\uc885\ub85c\ubd07 \uac1c\ubc1c(\ubb38\ud654\uccb4\uc721\uad00\uad11\ubd80, 2016)<\/li>
- VR \ucc29\uc6a9\uac10 \uac1c\uc120\uc744 \uc704\ud55c \uc5bc\uad74 \uac10\uac01 \uc778\uc9c0\ub2a5\ub825 \uce21\uc815(\uc0bc\uc131\uc804\uc790, 2016)<\/li>
- Haptics in Surgical Robot<\/strong><\/li><\/ul>\n\n\n\n
![\"\ucea1\ucc98\"](\"http:\/\/irobot.dgu.edu\/wordpress\/wp-content\/uploads\/2016\/06\/\ucea1\ucc98-300x160.jpg\")
<\/figure>\n\n\n\n![\"\ucea1\ucc983\"](\"http:\/\/irobot.dgu.edu\/wordpress\/wp-content\/uploads\/2016\/06\/\ucea1\ucc983-300x177.jpg\")
<\/figure>\n\n\n\n![\"\ucea1\ucc982\"](\"http:\/\/irobot.dgu.edu\/wordpress\/wp-content\/uploads\/2016\/06\/\ucea1\ucc982-300x206.jpg\")
<\/figure>\n\n\n\nWhen performing open surgery, surgeons use their touch sense intuitively in combination to get the information. However, during the minimally invasive laparoscopic robotic surgery with the conventional surgical robot, this haptic information can be lost because of the absence of force sensors in robot tools and haptic feedback instrument in master system. Sensors in the slave system and a combine tactile and kinesthetic feedback apparatus in the master system was developed to provide touch sense to surgeon in haptic feedback system of surgical robot. The combined tactile and kinesthetic feedback of the master device in robotic surgery improves the surgeon\u2019s ability to control the interaction force applied to the tissue.<\/p>\n\n\n\n
– \u201cGrip force measurement of forceps with fiber Bragg grating sensors\u201d, Electronics Letters<\/em>, vol 50, no 10, pp.733-735, 2014 (SCI) \u203b This paper was selected in the feature section in the front of Electronics Letters (vol 50, no 10)
– \u201cTactile Display with Tangential and Normal Skin Displacement for Robot-Assisted Surgery,\u201d Advanced Robotics<\/em>, vol 28, Issue 13, pp 859-868, 2014
– \u201cDevelopment of Flexible Three-Axis Tactile Sensor Based on Screen-Printed Carbon Nanotube-Polymer Composite\u201d, Journal of Micromechanics and Microengineering, vol 24, no 7
– \u201cRole of combined tactile and kinesthetic feedback in minimally invasive surgery\u201d, International Journal of Medical Robotics and Computer Assisted Surgery, Vol 11, Issue 3, pp 360\u2013374, 2015
– \u201cThree-axis pneumatic tactile display with integrated capacitive sensors for feedback control\u201d, Microsystem Technologies, Volume 22, Issue 2, pp 275-282
– \u201cPosition controlled pneumatic tactile display for tangential stimulation of a finger pad\u201d, Sensors and Actuators A: Physical, Volume 229, pp 15\u201322, 2015<\/p>\n\n\n\n- SmartWatch Interface<\/strong><\/li><\/ul>\n\n\n\n
![\"\ucea1\ucc986\"](\"http:\/\/irobot.dgu.edu\/wordpress\/wp-content\/uploads\/2016\/06\/\ucea1\ucc986-260x300.jpg\")
<\/figure>\n\n\n\n![\"\ucea1\ucc984\"](\"http:\/\/irobot.dgu.edu\/wordpress\/wp-content\/uploads\/2016\/06\/\ucea1\ucc984-300x225.jpg\")
<\/figure>\n\n\n\n![\"\ucea1\ucc985\"](\"http:\/\/irobot.dgu.edu\/wordpress\/wp-content\/uploads\/2016\/06\/\ucea1\ucc985-300x274.jpg\")
<\/figure>\n\n\n\nTouchscreen interaction has become a fundamental means of controlling mobile phones and smartwatches. However, the small form factor of a smartwatch limits the available interactive surface area. To overcome this limitation, we propose the expansion of the touch region of the screen to the back of the user\u2019s hand. We developed a touch module for sensing the touched finger position on the back of the hand using infrared (ir) line image sensors, based on the calibrated ir intensity and the maximum intensity region of an ir array.<\/p>\n\n\n\n
– \u201cExpansion of Smartwatch Touch Interface from Touchscreen to Around Device Interface Using Infrared Line Image Sensors\u201d, Sensors<\/em>, 15(7), pp16642-16653, 2015<\/p>\n\n\n\n
![\"\ucea1\ucc987\"](\"http:\/\/irobot.dgu.edu\/wordpress\/wp-content\/uploads\/2016\/06\/\ucea1\ucc987-300x225.jpg\")
<\/figure>\n\n\n\n![\"\ucea1\ucc988\"](\"http:\/\/irobot.dgu.edu\/wordpress\/wp-content\/uploads\/2016\/06\/\ucea1\ucc988-300x184.jpg\")
<\/figure>\n\n\n\nInspired by the mechanisms of bone conduction transmission, we present a novel sensor and actuation system that enables a smartwatch to securely communicate with a peripheral touch device, such as a smartphone. Our system regards hand structures as a mechanical waveguide that transmits particular signals through mechanical waves. As a signal, we used high-frequency vibrations (18.0\u201320.0 khz) so that users cannot sense the signals either tactually or audibly. To this end, we adopted a commercial surface transducer, which is originally developed as a bone-conduction actuator, for mechanical signal generation.<\/p>\n\n\n\n
– \u201cTransferring Data from Smartwatch to Smartphone through Mechanical Wave Propagation\u201d, Sensors<\/em>, 15(9), pp 21394-21406, 2015<\/p>\n\n\n\n
- Haptics (Interface)<\/strong><\/li><\/ul>\n\n\n\n
- Hip Force Exoskeleton<\/li>
- 360\ub3c4 3D \uce74\uba54\ub77c \ucd2c\uc601\uc744 \uc704\ud55c \ubaa8\ubc14\uc77c \ub85c\ubd07<\/li>
- VR \ud65c\uc6a9 3D CAD\ub97c \uc704\ud55c 3\ucc28\uc6d0 Interface<\/li>
- VR \uc7a5\uce58\ub97c \uc704\ud55c \uc5bc\uad74 \ubbfc\uac10\ub3c4 \uce21\uc815<\/li>
- Haptics (psycho-physical experiment)<\/strong><\/li><\/ul>\n\n\n\n
Beat perception on the Finger with two pin<\/em><\/p>\n\n\n\n
![\"\ucea1\ucc989\"](\"http:\/\/irobot.dgu.edu\/wordpress\/wp-content\/uploads\/2016\/06\/\ucea1\ucc989-217x300.jpg\")
<\/figure>\n\n\n\nTwo vibrations with slightly diVerent frequencies induce the beats phenomenon. In tactile perception, when two pins of diVerent frequencies stimulate the Wngertips, an individual perceives a beats caused by a summation stimulus of the two vibrations. The present study demonstrates experimentally that humans can perceive another vibration based on the beats phenomenon when two tactile stimuli with slightly diVerent frequencies are stimulated on the Wnger pad with a small contactor in diVerent locations at the same time. Moreover, we examined the amplitude of the detection threshold to be able to perceive beats phenomenon on the index Wnger with 5 carrier frequency (63.1, 100, 158.5, 251.2, and 398.1 Hz) and 4 beats frequency (2.5, 3.98, 6.31, and 10 Hz) when two stimuli 1 mm distance apart are vibrated at a slightly diVerent frequency. From the experiments, it is concluded that the amplitude threshold to be able to perceive beats decreases as the standard frequency increases under 398 Hz. Furthermore, from comparing the absolute detection threshold and beats detection threshold, as the carrier frequency increases, the required amplitude at two pins for the detection of beats decreases compared to absolute vibration.<\/p>\n\n\n\n
– “Effect of Frequency Difference on Sensitivity of Beat Perception.” Experimental Brain Research, vol 216, pp. 11-19, 2012<\/p>\n\n\n\n
Tactile Apparent Motion<\/em><\/p>\n\n\n\n
![\"\ucea1\ucc98a\"](\"http:\/\/irobot.dgu.edu\/wordpress\/wp-content\/uploads\/2016\/06\/\ucea1\ucc98a-300x214.jpg\")
<\/figure>\n\n\n\nThe effects of the frequency modulation of vibration elements on the representation of dynamic tactile apparent motion between both hands will be proposed. The sensation level difference due to the different frequencies that result when using vibrating motors on the right and left fingers causes a phantom sensation that is perceived as if the stimuli were between the fingers. The change of sensation level difference between both hands due to the frequency modulation creates a somatosensory illusion using this phantom sensation, which occurs in such a way as to feel like a vibration flow from one hand to the other hand.<\/p>\n\n\n\n
– \u201cTactile apparent motion between both hands based on frequency modulation,\u201d in haptics: perception, devices, mobility, and communication, springer, 2012, pp.293-300<\/p>\n\n\n\n
Shape Perception with frequency modulation<\/em><\/p>\n\n\n\n
![\"\ucea1\ucc9810\"](\"http:\/\/irobot.dgu.edu\/wordpress\/wp-content\/uploads\/2016\/06\/\ucea1\ucc9810-300x108.jpg\")
<\/figure>\n\n\n\n![\"\ucea1\ucc9811\"](\"http:\/\/irobot.dgu.edu\/wordpress\/wp-content\/uploads\/2016\/06\/\ucea1\ucc9811-300x75.jpg\")
<\/figure>\n\n\n\nThis study attempted to observe what effects the frequency modulation of vibration elements produce in representing a tactile shape. Tactile shapes were modulated based on frequency difference at constant amplitude through a tactile feedback array of 30 (5 \u00d7 6) pins, which stimulated the finger pad.<\/p>\n\n\n\n
– “Presentation of Surface Height Profiles Based on Frequency Modulation at Constant Amplitude Using Vibrotactile Elements.” Advanced Robotics, <\/em>vol 25, Issue 16, pp. 2065-2081, 2011<\/p>\n\n\n\n
- <\/li><\/ul>\n","protected":false},"excerpt":{"rendered":"
Deep-Learning \uc744 \ud65c\uc6a9\ud55c \ub85c\ubd07\uc758 Interaction Force \uc608\uce21(\uc0bc\uc131\uc804\uc790 \ubbf8\ub798\uc721\uc131\uc13c\ud1302017-2020)(Inferring Interaction Force of Robot from only Visual Information without Force\/Torque Sensor) \uc601\uc0c1 \uae30\ubc18\uc758 \uc785\ub825 \uac00\ub2a5\ud55c digital pen(\uad50\uc721\ubd80, 2018-2019) \ucd09\uac01 \uc13c\uc11c\ub97c \ud65c\uc6a9\ud55c \uc6d0\uaca9 \uc218\uc220\ub85c\ubd07\/\uc6d0\uaca9 \uc190 \uc81c\uc5b4 (\uc0b0\uc5c5\ud1b5\uc0c1\uc790\uc6d0\ubd80, 2017-2020) Proprioception(\uace0\uc720\uc218\uc6a9\uc131\uac10\uac01) \uce21\uc815\uc744 \uc704\ud55c \uc7a5\uce58 \uc124\uacc4 \ubc0f VR \ud65c\uc6a9 \uc2e4\ud5d8 (\ubcf4\uac74\ubcf5\uc9c0\ubd80,\uad6d\ub9bd\uc7ac\ud65c\uc6d0, 2017) Visual-tactile sensory perception (\uad50\uc721\ubd80, 2016-2018) 360\ub3c4 \uc601\uc0c1 \ucd2c\uc601\uc744 \uc704\ud55c… \ub354 \ubcf4\uae30 »Research_Past<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"neve_meta_sidebar":"","neve_meta_container":"","neve_meta_enable_content_width":"","neve_meta_content_width":0,"neve_meta_title_alignment":"","neve_meta_author_avatar":"","neve_post_elements_order":"","neve_meta_disable_header":"","neve_meta_disable_footer":"","neve_meta_disable_title":""},"_links":{"self":[{"href":"http:\/\/irobot.dgu.edu\/wordpress\/wp-json\/wp\/v2\/pages\/555"}],"collection":[{"href":"http:\/\/irobot.dgu.edu\/wordpress\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"http:\/\/irobot.dgu.edu\/wordpress\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"http:\/\/irobot.dgu.edu\/wordpress\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"http:\/\/irobot.dgu.edu\/wordpress\/wp-json\/wp\/v2\/comments?post=555"}],"version-history":[{"count":5,"href":"http:\/\/irobot.dgu.edu\/wordpress\/wp-json\/wp\/v2\/pages\/555\/revisions"}],"predecessor-version":[{"id":731,"href":"http:\/\/irobot.dgu.edu\/wordpress\/wp-json\/wp\/v2\/pages\/555\/revisions\/731"}],"wp:attachment":[{"href":"http:\/\/irobot.dgu.edu\/wordpress\/wp-json\/wp\/v2\/media?parent=555"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
- <\/li><\/ul>\n","protected":false},"excerpt":{"rendered":"
- Haptics (Interface)<\/strong><\/li><\/ul>\n\n\n\n
- SmartWatch Interface<\/strong><\/li><\/ul>\n\n\n\n
- \ub525\ub7ec\ub2dd\uc744 \uc0ac\uc6a9\ud55c \uacf5\uacf5\uae30\uc220\uc758 \uae30\uc220\uc0ac\uc5c5\ud654 \uc5ec\ubd80 \ud310\ub2e8 \ubaa8\ub378 \uac1c\ubc1c<\/strong>(KISTI, 2020)<\/li><\/ul>\n\n\n\n
- EMG\/EEG \uc2e0\ud638\ub97c \ud65c\uc6a9\ud55c Interaction force \uc608\uce21<\/strong><\/li><\/ul>\n\n\n\n
- \uace0\uc720\uc218\uc6a9\uc131 \uac10\uac01\uc758 \uce21\uc815 \ubc0f \uc0ac\uc6a9\uc790 \ud798\uc99d\uac15\uc744 \uc704\ud55c Exoskeleton \uac1c\ubc1c<\/strong><\/li><\/ul>\n\n\n\n
- \ub85c\ubd07 \uc6d0\uaca9\uc81c\uc5b4\uc2dc \ubb3c\ub9ac\uc801 \uc785\ub825\uac12\uc744 \ud65c\uc6a9\ud55c \uc2dc\uac04\uc9c0\uc5f0\uc5c6\ub294 \uc601\uc0c1 \uc0dd\uc131 \uae30\ubc95 \uac1c\ubc1c<\/strong>(\uacfc\ud559\uae30\uc220\ubd80-\uc911\uacac\uc5f0\uad6c, 2020~2023)<\/li><\/ul>\n\n\n\n