{"id":439,"date":"2020-05-25T16:38:49","date_gmt":"2020-05-25T07:38:49","guid":{"rendered":"http:\/\/irobot.dgu.edu\/?p=439"},"modified":"2020-05-25T16:38:49","modified_gmt":"2020-05-25T07:38:49","slug":"dae-kwan-ko-dcjournal-paper-accepted-ieee-transactions-on-industrial-informatics-continuous-image-generation-from-low-update-rate-images-and-physical-sensors-through-a-conditional-gan-for-robot","status":"publish","type":"post","link":"http:\/\/irobot.dgu.edu\/wordpress\/dae-kwan-ko-dcjournal-paper-accepted-ieee-transactions-on-industrial-informatics-continuous-image-generation-from-low-update-rate-images-and-physical-sensors-through-a-conditional-gan-for-robot\/","title":{"rendered":"Dae-Kwan Ko : Journal Paper Accepted (IEEE Transactions on Industrial Informatics)"},"content":{"rendered":"
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Continuous Image Generation from Low-Update-Rate Images and Physical Sensors through a Conditional GAN for Robot Teleoperation<\/strong><\/div>\n<\/div>\n<\/div>\n
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Dae-Kwan Ko ; Dong-Han Lee ; Soo-Chul Lim<\/div>\n
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Abstract:<\/strong><\/p>\n

When a robot is teleoperated, its operator control is based on transmitted images. Network limitations and\/or a remote distance usually cause delays or interruptions of the image transmission, which is one of the reasons for the instability of teleoperation systems. In this work, we propose a high-update-rate image generation method using past low update image and current grip position and electrical motor current of gripper received by sensors during teleoperation via a conditional generative adversarial network. The main challenge is that such a network can generate current high-update-rate images from past low-update-rate one, the current high-update-rate grip force, and the grip angle. We equipped a robot gripper with a camera and a grip force sensor and collected a large dataset of robot vision, grip force, and grip angle sequences; objects with deformation, including irregular deformation, and rigid objects were tested in the experiment to verify the possibility of high-update-rate image generation under various grip conditions. We found that the proposed network allows the generation of current images with high update rate. Here, we present the results of real-time image generation from delayed images and sensor data along with the root-mean-square value, the peak signal-to-noise ratio, and the structural similarity index measure and compare the images generated by the proposed network with those from other networks.<\/div>\n<\/div>\n<\/div>\n<\/div>\n
Published in:\u00a0<\/strong>IEEE Transactions on Industrial Informatics<\/a>\u00a0( Early Access )<\/div>\n
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Page(s):\u00a0<\/strong>1\u00a0– 1<\/div>\n
Date of Publication:<\/strong>\u00a006 May 2020\u00a0<\/i><\/div>\n
DOI:\u00a0<\/strong>10.1109\/TII.2020.2991764<\/a><\/div>\n<\/div>\n
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Publisher:<\/strong>\u00a0IEEE<\/span><\/div>\n
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Continuous Image Generation from Low-Update-Rate Images and Physical Sensors through a Conditional GAN for Robot Teleoperation Dae-Kwan Ko ; Dong-Han Lee ; Soo-Chul Lim   Abstract: When a robot is teleoperated, its operator control is based on transmitted images. Network limitations and\/or a remote distance usually cause delays or interruptions of the image transmission, which… \ub354 \ubcf4\uae30 »Dae-Kwan Ko : Journal Paper Accepted (IEEE Transactions on Industrial Informatics)<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","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":""},"categories":[1],"tags":[],"_links":{"self":[{"href":"http:\/\/irobot.dgu.edu\/wordpress\/wp-json\/wp\/v2\/posts\/439"}],"collection":[{"href":"http:\/\/irobot.dgu.edu\/wordpress\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/irobot.dgu.edu\/wordpress\/wp-json\/wp\/v2\/types\/post"}],"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=439"}],"version-history":[{"count":0,"href":"http:\/\/irobot.dgu.edu\/wordpress\/wp-json\/wp\/v2\/posts\/439\/revisions"}],"wp:attachment":[{"href":"http:\/\/irobot.dgu.edu\/wordpress\/wp-json\/wp\/v2\/media?parent=439"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/irobot.dgu.edu\/wordpress\/wp-json\/wp\/v2\/categories?post=439"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/irobot.dgu.edu\/wordpress\/wp-json\/wp\/v2\/tags?post=439"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}