BEGIN:VCALENDAR
VERSION:2.0
PRODID:IEEE vTools.Events//EN
CALSCALE:GREGORIAN
BEGIN:VTIMEZONE
TZID:Asia/Kolkata
BEGIN:STANDARD
DTSTART:19451014T230000
TZOFFSETFROM:+0630
TZOFFSETTO:+0530
TZNAME:IST
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BEGIN:VEVENT
DTSTAMP:20251230T154435Z
UID:926E9947-724E-4684-9C6C-FDB6D976A440
DTSTART;TZID=Asia/Kolkata:20231127T110000
DTEND;TZID=Asia/Kolkata:20231127T120000
DESCRIPTION:Abstract :\n\nThis talk introduces the latest spatial AI-based 
 autonomous navigation technologies widely used for autonomous vehicles\, s
 uch as mobile robots\, legged robots\, self-driving cars\, and drones. In 
 addition to the technical background of SLAM (Simultaneous Localization An
 d Mapping)\, path planning\, and motion control\, actual cases developed b
 y KAIST Urban Robotics Lab will be introduced. Specifically\, we present v
 arious navigation frameworks with mobile robots\, drones\, and legged robo
 ts in diverse environments\, including rough terrains. The latest developm
 ent of the deep reinforcement learning-based blind locomotion technology c
 alled DreamWaQ will also be introduced.\n\nSpeaker(s): Hyun Myung\, Ph.D. 
 \, \n\nVirtual: https://events.vtools.ieee.org/m/383505
LOCATION:Virtual: https://events.vtools.ieee.org/m/383505
ORGANIZER:brindhamit@gmail.com
SEQUENCE:22
SUMMARY:IEEE VTS DLP Talk on INTELLIGENT AUTONOMOUS NAVIGATION OF ROBOTS
URL;VALUE=URI:https://events.vtools.ieee.org/m/383505
X-ALT-DESC:Description: <br /><p>Abstract :</p>\n<p>This talk introduces th
 e latest spatial AI-based autonomous navigation technologies widely used f
 or autonomous vehicles\, such as mobile robots\, legged robots\, self-driv
 ing cars\, and drones. In addition to the technical background of SLAM (Si
 multaneous Localization And Mapping)\, path planning\, and motion control\
 , actual cases developed by KAIST Urban Robotics Lab will be introduced. S
 pecifically\, we present various navigation frameworks with mobile robots\
 , drones\, and legged robots in diverse environments\, including rough ter
 rains. The latest development of the deep reinforcement learning-based bli
 nd locomotion technology called DreamWaQ will also be introduced.</p>\n<p>
 &nbsp\;</p>
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