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DTSTART:20260308T030000
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DTSTAMP:20260417T031753Z
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DTSTART;TZID=America/Denver:20260416T170000
DTEND;TZID=America/Denver:20260416T181500
DESCRIPTION:Join us for the upcoming technical talk —attend in person at 
 Stockman’s Restaurant or virtually via [Microsoft Teams](https://teams.m
 icrosoft.com/l/meetup-join/19%3ameeting_MGYxYTkzNmMtMzg0MS00MjdjLTkwYmMtOW
 NkMWMwNjMzOWFi%40thread.v2/0?context=%7b%22Tid%22%3a%224cf464b7-869a-4236-
 8da2-a98566485554%22%2c%22Oid%22%3a%2264d770c8-e8c2-4ef1-b2f4-1e7ebd03bd37
 %22%7d)\n\nTitle:\n\nDigital Twins of Radioactive Environments: EV-Powered
  Robotics and Sensor Fusion in Inaccessible Zones\n\nAbstract:\n\nNuclear 
 waste repositories present significant infrastructure monitoring challenge
 s due to hazardous conditions and restricted human access. This talk prese
 nts the design\, prototyping\, and field deployment of an integrated mobil
 e robotics platform developed for generating high-fidelity digital twins o
 f inaccessible nuclear storage environments.\n\nThe system integrates an e
 lectric vehicle providing sustained field-deployable power and base statio
 n functionality\, a quadruped robot capable of navigating confined and irr
 egular terrain\, and custom sensing and edge-computing modules incorporati
 ng 3D LiDAR\, high-resolution visual cameras\, and environmental monitorin
 g sensors. Together\, these components enable extended autonomous inspecti
 on missions across full operational shifts.\n\nPost-processing algorithms 
 fuse multi-modal sensor streams to produce accurate 3D digital twin models
  of facility structures\, supporting remote visualization and condition as
 sessment without personnel exposure. The platform has been validated throu
 gh deployment at a Department of Energy nuclear waste storage facility\, d
 emonstrating reliable terrain traversal\, comprehensive data acquisition\,
  and accurate facility reconstruction.\n\nThe talk will also touch on less
 ons learned from real-world deployment and the broader applicability of th
 is framework to hazardous site characterization and nuclear decommissionin
 g operations. Questions and discussion welcome.\n\nSpeaker: Pengcheng Cao\
 n\nPengcheng Cao is a Postdoctoral Research Associate with the Physical Pr
 ocess Science &amp; Realization group of the EES&amp;T Department. He holds a Ph.D
 . degree in Mechanical Engineering from UC San Diego and a Master&#39;s degree
  in Computer Science from Arizona State University. His research interests
  span robotics in hazardous environments\, data-driven digital twin modeli
 ng\, and control system stabilities. He has over 10 scientific publication
 s and 6 contributed talks. While working at INL\, he is also serving as th
 e Professional Activities Chair of IEEE Eastern Idaho Section.\n\nCo-spons
 ored by: INL-Idaho National Lab\n\n1175 Pier View Dr\, Idaho Falls\, Idaho
 \, United States\, 83402\, Virtual: https://events.vtools.ieee.org/m/55263
 9
LOCATION:1175 Pier View Dr\, Idaho Falls\, Idaho\, United States\, 83402\, 
 Virtual: https://events.vtools.ieee.org/m/552639
ORGANIZER:crnaik@ieee.org
SEQUENCE:19
SUMMARY:Brew with the Crew: Digital Twins of Radioactive Environments: EV-P
 owered Robotics and Sensor Fusion in Inaccessible Zones
URL;VALUE=URI:https://events.vtools.ieee.org/m/552639
X-ALT-DESC:Description: &lt;br /&gt;&lt;p class=&quot;MsoNormal&quot;&gt;&lt;em&gt;Join us for the upco
 ming technical talk &amp;mdash\;attend in person at Stockman&amp;rsquo\;s Restaura
 nt or virtually via&amp;nbsp\;&lt;a href=&quot;https://teams.microsoft.com/l/meetup-jo
 in/19%3ameeting_MGYxYTkzNmMtMzg0MS00MjdjLTkwYmMtOWNkMWMwNjMzOWFi%40thread.
 v2/0?context=%7b%22Tid%22%3a%224cf464b7-869a-4236-8da2-a98566485554%22%2c%
 22Oid%22%3a%2264d770c8-e8c2-4ef1-b2f4-1e7ebd03bd37%22%7d&quot;&gt;Microsoft Teams&amp;
 nbsp\;&lt;/a&gt;&lt;/em&gt;&lt;/p&gt;\n&lt;p class=&quot;MsoNormal&quot;&gt;&lt;strong&gt;Title:&lt;/strong&gt;&lt;/p&gt;\n&lt;p 
 data-pm-slice=&quot;1 1 []&quot;&gt;Digital Twins of Radioactive Environments: EV-Power
 ed Robotics and Sensor Fusion in Inaccessible Zones&lt;/p&gt;\n&lt;p class=&quot;MsoNorm
 al&quot;&gt;&lt;strong&gt;Abstract: &lt;/strong&gt;&lt;/p&gt;\n&lt;p class=&quot;MsoNormal&quot;&gt;Nuclear waste re
 positories present significant infrastructure monitoring challenges due to
  hazardous conditions and restricted human access. This talk presents the 
 design\, prototyping\, and field deployment of an integrated mobile roboti
 cs platform developed for generating high-fidelity digital twins of inacce
 ssible nuclear storage environments.&lt;/p&gt;\n&lt;p class=&quot;MsoNormal&quot;&gt;The system 
 integrates an electric vehicle providing sustained field-deployable power 
 and base station functionality\, a quadruped robot capable of navigating c
 onfined and irregular terrain\, and custom sensing and edge-computing modu
 les incorporating 3D LiDAR\, high-resolution visual cameras\, and environm
 ental monitoring sensors. Together\, these components enable extended auto
 nomous inspection missions across full operational shifts.&lt;/p&gt;\n&lt;p class=&quot;
 MsoNormal&quot;&gt;Post-processing algorithms fuse multi-modal sensor streams to p
 roduce accurate 3D digital twin models of facility structures\, supporting
  remote visualization and condition assessment without personnel exposure.
  The platform has been validated through deployment at a Department of Ene
 rgy nuclear waste storage facility\, demonstrating reliable terrain traver
 sal\, comprehensive data acquisition\, and accurate facility reconstructio
 n.&lt;/p&gt;\n&lt;p class=&quot;MsoNormal&quot;&gt;The talk will also touch on lessons learned f
 rom real-world deployment and the broader applicability of this framework 
 to hazardous site characterization and nuclear decommissioning operations.
  Questions and discussion welcome.&lt;/p&gt;\n&lt;p&gt;&amp;nbsp\;&lt;/p&gt;\n&lt;p&gt;&lt;strong&gt;Speaker
 :&lt;/strong&gt; Pengcheng Cao&lt;/p&gt;\n&lt;p&gt;&lt;img src=&quot;https://events.vtools.ieee.org/
 vtools_ui/media/display/d8464799-1cfa-484e-9e3b-365aa13af05b&quot;&gt;&lt;/p&gt;\n&lt;p&gt;Pen
 gcheng Cao is a Postdoctoral Research Associate with the Physical Process 
 Science &amp;amp\; Realization group of the EES&amp;amp\;T Department. He holds a 
 Ph.D. degree in Mechanical Engineering from UC San Diego and a Master&#39;s de
 gree in Computer Science from Arizona State University. His research inter
 ests span robotics in hazardous environments\, data-driven digital twin mo
 deling\, and control system stabilities. He has over 10 scientific publica
 tions and 6 contributed talks. While working at INL\, he is also serving a
 s the Professional Activities Chair of IEEE Eastern Idaho Section.&lt;/p&gt;\n&lt;p
 &gt;&amp;nbsp\;&lt;/p&gt;\n&lt;p&gt;&amp;nbsp\;&lt;/p&gt;\n&lt;p&gt;&amp;nbsp\;&lt;/p&gt;\n&lt;p&gt;&amp;nbsp\;&lt;/p&gt;\n&lt;p&gt;&amp;nbsp\;&lt;/
 p&gt;\n&lt;p&gt;&amp;nbsp\;&lt;/p&gt;\n&lt;p&gt;&amp;nbsp\;&lt;/p&gt;\n&lt;p&gt;&amp;nbsp\;&lt;/p&gt;\n&lt;p&gt;&amp;nbsp\;&lt;/p&gt;\n&lt;p&gt;&amp;nb
 sp\;&lt;/p&gt;
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