{"id":4625,"date":"2020-06-24T14:43:32","date_gmt":"2020-06-24T06:43:32","guid":{"rendered":"http:\/\/pairlabs.ai.pro6.designworks.tw\/?post_type=portfolio&#038;p=4625"},"modified":"2020-07-22T14:37:18","modified_gmt":"2020-07-22T06:37:18","slug":"on-self-maneuvered-patrolling-robots-with-artificial-intelligence-and-multi-sensory-data-fusion-technology-p-en","status":"publish","type":"portfolio","link":"https:\/\/pairlabs.ai\/en\/portfolio-item\/on-self-maneuvered-patrolling-robots-with-artificial-intelligence-and-multi-sensory-data-fusion-technology-p-en\/","title":{"rendered":"On Self-Maneuvered Patrolling Robots with Artificial Intelligence and Multi-Sensory Data Fusion Technology"},"content":{"rendered":"<\/div><\/div><\/div><!-- close content main div --><\/div><\/div><div id='av_section_1' class='avia-section main_color avia-section-large avia-no-border-styling avia-full-stretch av-section-color-overlay-active avia-bg-style-fixed    av-small-hide av-mini-hide container_wrap sidebar_right' style='background-repeat: no-repeat; background-image: url(https:\/\/pairlabs.ai\/wp-content\/uploads\/2020\/05\/wall005.jpg);background-attachment: fixed; background-position: bottom right;  '  data-section-bg-repeat='stretch' style='background-repeat: no-repeat; background-image: url(https:\/\/pairlabs.ai\/wp-content\/uploads\/2020\/05\/wall005.jpg);background-attachment: fixed; background-position: bottom right;  ' ><div class='av-section-color-overlay-wrap'><div class='av-section-color-overlay' style='opacity: 0.6; background-color: #ffffff; '><\/div><div class='container' ><div class='template-page content  av-content-small alpha units'><div class='post-entry post-entry-type-page post-entry-4625'><div class='entry-content-wrapper clearfix'>\n<div class='flex_column_table av-equal-height-column-flextable -flextable' style='margin-top:0px; margin-bottom:-20px; '><div class=\"flex_column av_one_fourth  flex_column_table_cell av-equal-height-column av-align-top av-zero-column-padding first   \" style='border-radius:0px; '><\/div><\/div><!--close column table wrapper. Autoclose: 1 --><div class='flex_column_table av-equal-height-column-flextable -flextable' style='margin-top:0px; margin-bottom:-20px; '><div class='av-flex-placeholder'><\/div><div class=\"flex_column av_one_half  flex_column_table_cell av-equal-height-column av-align-top av-zero-column-padding   \" style='border-radius:0px; '><section class=\"av_textblock_section \"  itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/CreativeWork\" ><div class='avia_textblock  '  style='font-size:20px; '  itemprop=\"text\" ><p style=\"text-align: center;\">Pervasive Artificial Intelligence Research (PAIR) Labs<\/p>\n<\/div><\/section><br \/>\n<div style='height:20px' class='hr hr-invisible   '><span class='hr-inner ' ><span class='hr-inner-style'><\/span><\/span><\/div><\/p><\/div><\/div><!--close column table wrapper. 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Autoclose: 1 --><div class='flex_column_table av-equal-height-column-flextable -flextable' ><div class='av-flex-placeholder'><\/div><div class=\"flex_column av_one_half  flex_column_table_cell av-equal-height-column av-align-top    \" style='background-color:#00a0e9; background:linear-gradient(to bottom right,#00a0e9,#25a98f); padding:10px; border-radius:0px; '><p><div style=' margin-top:-21px; margin-bottom:0px;'  class='hr hr-custom hr-center hr-icon-yes   '><span class='hr-inner   inner-border-av-border-thin' style=' width:0px;' ><span class='hr-inner-style'><\/span><\/span><span class='av-seperator-icon' style='color:#ffffff;' aria-hidden='true' data-av_icon='\ue883' data-av_iconfont='entypo-fontello'><\/span><span class='hr-inner   inner-border-av-border-thin' style=' width:0px;' ><span class='hr-inner-style'><\/span><\/span><\/div><br \/>\n<section class=\"av_textblock_section \"  itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/CreativeWork\" ><div class='avia_textblock  av_inherit_color '  style='font-size:30px; color:#ffffff; '  itemprop=\"text\" ><h1 style=\"text-align: center;\">Robotics and sensing technology Team<\/h1>\n<\/div><\/section><\/p><\/div><\/div><!--close column table wrapper. Autoclose: 1 --><div class='flex_column_table av-equal-height-column-flextable -flextable' ><div class='av-flex-placeholder'><\/div><div class=\"flex_column av_one_fourth  flex_column_table_cell av-equal-height-column av-align-top av-zero-column-padding   \" style='border-radius:0px; '><\/div><\/div><!--close column table wrapper. Autoclose: 1 -->\n<\/div><\/div><\/div><!-- close content main div --><\/div><\/div><\/div><div id='after_section_1' class='main_color av_default_container_wrap container_wrap sidebar_right' style=' '   style=' ' ><div class='container' ><div class='template-page content  av-content-small alpha units'><div class='post-entry post-entry-type-page post-entry-4625'><div class='entry-content-wrapper clearfix'>\n<\/div><\/div><\/div><!-- close content main div --><\/div><\/div><div id='av_section_2' class='avia-section main_color avia-section-large avia-no-border-styling avia-full-stretch av-section-color-overlay-active avia-bg-style-fixed    av-desktop-hide av-medium-hide container_wrap sidebar_right' style='background-repeat: no-repeat; background-image: url(https:\/\/pairlabs.ai\/wp-content\/uploads\/2020\/05\/wall005.jpg);background-attachment: fixed; background-position: bottom right;  '  data-section-bg-repeat='stretch' style='background-repeat: no-repeat; background-image: url(https:\/\/pairlabs.ai\/wp-content\/uploads\/2020\/05\/wall005.jpg);background-attachment: fixed; background-position: bottom right;  ' ><div class='av-section-color-overlay-wrap'><div class='av-section-color-overlay' style='opacity: 0.6; background-color: #ffffff; '><\/div><div class='container' ><div class='template-page content  av-content-small alpha units'><div class='post-entry post-entry-type-page post-entry-4625'><div class='entry-content-wrapper clearfix'>\n<div class='flex_column_table av-equal-height-column-flextable -flextable' style='margin-top:0px; margin-bottom:-20px; '><div class=\"flex_column av_one_fourth  flex_column_table_cell av-equal-height-column av-align-top av-zero-column-padding first   \" style='border-radius:0px; '><\/div><\/div><!--close column table wrapper. Autoclose: 1 --><div class='flex_column_table av-equal-height-column-flextable -flextable' style='margin-top:0px; margin-bottom:-20px; '><div class='av-flex-placeholder'><\/div><div class=\"flex_column av_one_half  flex_column_table_cell av-equal-height-column av-align-top av-zero-column-padding   \" style='border-radius:0px; '><section class=\"av_textblock_section \"  itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/CreativeWork\" ><div class='avia_textblock  '  style='font-size:20px; '  itemprop=\"text\" ><p style=\"text-align: center;\">Pervasive Artificial Intelligence Research (PAIR) Labs<\/p>\n<\/div><\/section><br \/>\n<div style='height:1px' class='hr hr-invisible   '><span class='hr-inner ' ><span class='hr-inner-style'><\/span><\/span><\/div><\/p><\/div><\/div><!--close column table wrapper. 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Autoclose: 1 --><div class='flex_column_table av-equal-height-column-flextable -flextable' ><div class='av-flex-placeholder'><\/div><div class=\"flex_column av_one_half  flex_column_table_cell av-equal-height-column av-align-top    \" style='background-color:#00a0e9; background:linear-gradient(to bottom right,#00a0e9,#25a98f); padding:10px; border-radius:0px; '><p><div style=' margin-top:-21px; margin-bottom:0px;'  class='hr hr-custom hr-center hr-icon-yes   '><span class='hr-inner   inner-border-av-border-thin' style=' width:0px;' ><span class='hr-inner-style'><\/span><\/span><span class='av-seperator-icon' style='color:#ffffff;' aria-hidden='true' data-av_icon='\ue883' data-av_iconfont='entypo-fontello'><\/span><span class='hr-inner   inner-border-av-border-thin' style=' width:0px;' ><span class='hr-inner-style'><\/span><\/span><\/div><br \/>\n<section class=\"av_textblock_section \"  itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/CreativeWork\" ><div class='avia_textblock  av_inherit_color '  style='font-size:30px; color:#ffffff; '  itemprop=\"text\" ><h2 style=\"text-align: center;\">Robotics and sensing technology Team<\/h2>\n<\/div><\/section><\/p><\/div><\/div><!--close column table wrapper. Autoclose: 1 --><div class='flex_column_table av-equal-height-column-flextable -flextable' ><div class='av-flex-placeholder'><\/div><div class=\"flex_column av_one_fourth  flex_column_table_cell av-equal-height-column av-align-top av-zero-column-padding   \" style='border-radius:0px; '><\/div><\/div><!--close column table wrapper. Autoclose: 1 -->\n<\/div><\/div><\/div><!-- close content main div --><\/div><\/div><\/div><div id='after_section_2' class='main_color av_default_container_wrap container_wrap sidebar_right' style=' '   style=' ' ><div class='container' ><div class='template-page content  av-content-small alpha units'><div class='post-entry post-entry-type-page post-entry-4625'><div class='entry-content-wrapper clearfix'>\n<\/div><\/div><\/div><!-- close content main div --><\/div><\/div><div id='av_section_3' class='avia-section socket_color avia-section-default avia-no-border-styling avia-bg-style-scroll    av-arrow-down-section container_wrap sidebar_right' style=' '   style=' ' ><div class='container' ><div class='template-page content  av-content-small alpha units'><div class='post-entry post-entry-type-page post-entry-4625'><div class='entry-content-wrapper clearfix'>\n<div style='padding-bottom:0px; margin:0 0 0 0; font-size:30px;' class='av-special-heading av-special-heading-h3  blockquote modern-quote modern-centered   av-inherit-size '><h3 class='av-special-heading-tag '  itemprop=\"headline\"  >On Self-Maneuvered Patrolling Robots with Artificial Intelligence and Multi-Sensory Data Fusion Technology<\/h3><div class='special-heading-border'><div class='special-heading-inner-border' ><\/div><\/div><\/div>\n<\/div><\/div><\/div><!-- close content main div --><\/div><div class='av-extra-border-element border-extra-arrow-down'><div class='av-extra-border-outer'><div class='av-extra-border-inner'  style='background-color:#333333;' ><\/div><\/div><\/div><\/div><div id='after_section_3' class='main_color av_default_container_wrap container_wrap sidebar_right' style=' '   style=' ' ><div class='container' ><div class='template-page content  av-content-small alpha units'><div class='post-entry post-entry-type-page post-entry-4625'><div class='entry-content-wrapper clearfix'>\n<\/div><\/div><\/div><!-- close content main div --><\/div><\/div><div id='av_section_4' class='avia-section main_color avia-section-default avia-no-border-styling avia-bg-style-scroll   container_wrap sidebar_right' style=' '   style=' ' ><div class='container' ><div class='template-page content  av-content-small alpha units'><div class='post-entry post-entry-type-page post-entry-4625'><div class='entry-content-wrapper clearfix'>\n<div class=\"flex_column av_three_fifth  flex_column_div av-zero-column-padding first  \" style='border-radius:0px; '><section class=\"av_textblock_section \"  itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/CreativeWork\" ><div class='avia_textblock  '   itemprop=\"text\" ><p><b>Principal Investigator:<\/b><a href=\"http:\/\/pairlabs.ai\/\/en\/2018\/04\/21\/professor-yu-chee-tseng\/\">Professor Yu-Chee Tseng<\/a><\/p>\n<p>&#8212;<\/p>\n<blockquote>\n<h5><b>Summary<\/b><\/h5>\n<\/blockquote>\n<p>In this project, we focus on the development of AI and multi-sensory data fusion technology. Based on the developed approaches, we can improve machine (i.e., robot) perception in a smart environment and increase the intelligence of robots. The core research topic here is how to utilize artificial intelligence to carry out a wide range of sensory data analysis, and then extract high-level information to enhance the efficiency of work as well as provide advanced robot-human services. The proposed system is able to recognize people even without capturing human biological features.<\/p>\n<blockquote>\n<h5><b>Keywords<\/b><\/h5>\n<\/blockquote>\n<p>Image Recognition, Depth Learning, Indoor Localization, Inertial Sensor, Sensor Fusion, Robot, ROS<\/p>\n<blockquote>\n<h5><b>Innovations<\/b><\/h5>\n<\/blockquote>\n<ul>\n<li><b>[Supervision capability] Fusion of surveillance camera (RGB) and location data.<\/b>\u00a0We design a pairing mechanism to couple human objects with their IDs. The pairing results of PID (Person identification) can be visualized on a screen. A prototype system is developed and extensive experiments are conducted to analyze the correctness of tagging results.<\/li>\n<li><b>[Third Eye] Fusion of depth camera (RGB-D) and inertial sensor data.<\/b>\u00a0We develop person identification system with wearable devices and RGB-D camera. The depth camera can capture the skeleton data of these people. Each person wears an inertial sensor, which can capture the motions of the user. The skeleton and inertial data are collected and transmitted to our fusion server. The goal is to pair each inertial data with a skeleton. Finally, we can tag the IDs of skeletons in the visualization result.<\/li>\n<\/ul>\n<blockquote>\n<h5><b>Benefits<\/b><\/h5>\n<\/blockquote>\n<ul>\n<li>Supervision capability: Through fusing location trajectories of video data and iBeacon data, we are able to achieve PID on long-distance cameras.<\/li>\n<li>Third Eye: Through fusing skeleton data from RGB-D camera and motion data from wearable inertial measuring unit, we are able to achieve short-distance, highly accurate PID.<\/li>\n<li>Other on-going Researches\n<ol>\n<li>Building a robot platform, which enables the robot to track a specific person, climb up and down stairs. Fig. 3 shows the structure of the tracking robot we are working on with Prof. Wayne Wang (NTNU).<\/li>\n<li>Demonstrating the approaches for multi-sensory fusion in V2V (Vehicle-to-Vehicle) communications. Fig. 4 shows the V2V data fusion results.<\/li>\n<\/ol>\n<\/li>\n<\/ul>\n<\/div><\/section><\/div><div class=\"flex_column av_two_fifth  flex_column_div av-zero-column-padding   \" style='border-radius:0px; '><p><div class='avia-progress-bar-container  av-desktop-hide av-medium-hide av-small-hide av-mini-hide avia_animate_when_almost_visible   av-striped-bar av-animated-bar '><div class='avia-progress-bar theme-color-bar icon-bar-no'><div class='progressbar-title-wrap'><div class='progressbar-icon'><span class='progressbar-char' aria-hidden='true' data-av_icon='\ue856' data-av_iconfont='entypo-fontello'><\/span><\/div><div class='progressbar-title'>Type 1<\/div><\/div><div class='progress' ><div class='bar-outer'><div class='bar' style='width: 91%' data-progress='91'><\/div><\/div><\/div><\/div><div class='avia-progress-bar theme-color-bar icon-bar-no'><div class='progressbar-title-wrap'><div class='progressbar-icon'><span class='progressbar-char' aria-hidden='true' data-av_icon='\ue856' data-av_iconfont='entypo-fontello'><\/span><\/div><div class='progressbar-title'>Type 2<\/div><\/div><div class='progress' ><div class='bar-outer'><div class='bar' style='width: 86%' data-progress='86'><\/div><\/div><\/div><\/div><div class='avia-progress-bar theme-color-bar icon-bar-no'><div class='progressbar-title-wrap'><div class='progressbar-icon'><span class='progressbar-char' aria-hidden='true' data-av_icon='\ue856' data-av_iconfont='entypo-fontello'><\/span><\/div><div class='progressbar-title'>Type 3<\/div><\/div><div class='progress' ><div class='bar-outer'><div class='bar' style='width: 97%' data-progress='97'><\/div><\/div><\/div><\/div><div class='avia-progress-bar theme-color-bar icon-bar-no'><div class='progressbar-title-wrap'><div class='progressbar-icon'><span class='progressbar-char' aria-hidden='true' data-av_icon='\ue856' data-av_iconfont='entypo-fontello'><\/span><\/div><div class='progressbar-title'>Type 4<\/div><\/div><div class='progress' ><div class='bar-outer'><div class='bar' style='width: 85%' data-progress='85'><\/div><\/div><\/div><\/div><\/div><br \/>\n<div style='height:20px' class='hr hr-invisible   '><span class='hr-inner ' ><span class='hr-inner-style'><\/span><\/span><\/div><br \/>\n<div id='av-masonry-1' class='av-masonry  noHover av-fixed-size av-no-gap av-hover-overlay- av-masonry-animation-active av-masonry-col-2 av-caption-always av-caption-style- av-masonry-gallery   av-orientation-portrait   av-medium-columns-overwrite av-medium-columns-2 av-small-columns-overwrite av-small-columns-2 av-mini-columns-overwrite av-mini-columns-2'  ><div class='av-masonry-container isotope av-js-disabled ' ><div class='av-masonry-entry isotope-item av-masonry-item-no-image '><\/div><a href=\"https:\/\/pairlabs.ai\/wp-content\/uploads\/2020\/06\/\u66fe\u715c\u68cb-1-773x1030.jpg\" id='av-masonry-1-item-5109' data-av-masonry-item='5109' class='av-masonry-entry isotope-item post-5109 attachment type-attachment status-inherit hentry  av-masonry-item-with-image' title=\"\u66fe\u715c\u68cb\"  itemprop=\"thumbnailUrl\" ><div class='av-inner-masonry-sizer'><\/div><figure class='av-inner-masonry main_color'><div class=\"av-masonry-outerimage-container\"><div class=\"av-masonry-image-container\" style=\"background-image: url(https:\/\/pairlabs.ai\/wp-content\/uploads\/2020\/06\/\u66fe\u715c\u68cb-1-529x705.jpg);\" title=\"\u66fe\u715c\u68cb\" ><\/div><\/div><\/figure><\/a><!--end av-masonry entry--><\/div><\/div><\/p><\/div><\/div><\/div><\/div><!-- close content main div --><\/div><\/div><div id='after_section_4' class='main_color av_default_container_wrap container_wrap sidebar_right' style=' '   style=' ' ><div class='container' ><div class='template-page content  av-content-small alpha units'><div class='post-entry post-entry-type-page post-entry-4625'><div class='entry-content-wrapper clearfix'><\/div><\/div><\/div><!-- close content main div --><\/div><\/div><div id='av_section_5' class='avia-section alternate_color avia-section-default avia-no-border-styling avia-bg-style-scroll    container_wrap sidebar_right' style=' '   style=' ' ><div class='container' ><div class='template-page content  av-content-small alpha units'><div class='post-entry post-entry-type-page post-entry-4625'><div class='entry-content-wrapper clearfix'>\n<div class='flex_column_table av-equal-height-column-flextable -flextable' ><div class=\"flex_column av_two_fifth  flex_column_table_cell av-equal-height-column av-align-middle av-zero-column-padding first   \" style='border-radius:0px; 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