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DTSTART:20231105T010000
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UID:4B272398-FD04-4DBC-BD0F-D2ACE7A2840F
DTSTART;TZID=America/Denver:20230517T180000
DTEND;TZID=America/Denver:20230517T200000
DESCRIPTION:Presentation: Bridging The Gap Between Robots and Humans Throug
 h Explainability\n\nAbstract:\n\nRobots are traditionally placed behind fe
 nces for autonomous pick-and-place tasks. Today\, we are witnessing robots
  moving to work with humans. They will not only need to manipulate but als
 o hand objects to people and explain when autonomy fails. In this talk\, I
  will start with how I tackled challenges in mobile manipulation tasks in 
 a collaborative environment and a better way to let objects go for fluent 
 human-robot handovers. Then I will focus on high-level hierarchical explan
 ation generation algorithms using behavior trees and finer-level reference
 s for preferred concise explanations. This includes reference production t
 hrough a cognitive status-informed approach and mixed-reality robot behavi
 or replays to reason about objects no longer present. Finally\, I will dis
 cuss how augmented reality can enable physically limited robots to gesture
 .\n\nCo-sponsored by: Eric Ericson\n\nSpeaker(s): Dr. Zhao Han\, \n\nRoom:
  410\, Bldg: Ritchie Engineering\, 2155 East Wesley Avenue\, Denver\, Colo
 rado\, United States\, 80208
LOCATION:Room: 410\, Bldg: Ritchie Engineering\, 2155 East Wesley Avenue\, 
 Denver\, Colorado\, United States\, 80208
ORGANIZER:gowansj@ieee.org
SEQUENCE:3
SUMMARY:CIS: Bridging The Gap Between Robots and Humans Through Explainabil
 ity
URL;VALUE=URI:https://events.vtools.ieee.org/m/358498
X-ALT-DESC:Description: <br /><div class="presentation-title"><strong>Prese
 ntation: Bridging The Gap Between Robots and Humans Through Explainability
  </strong></div>\n<div class="abstract">\n<p><strong>Abstract:</strong></p
 >\n<p>Robots are traditionally placed behind fences for autonomous pick-an
 d-place tasks. Today\, we are witnessing robots moving to work with humans
 . They will not only need to manipulate but also hand objects to people an
 d explain when autonomy fails. In this talk\, I will start with how I tack
 led challenges in mobile manipulation tasks in a collaborative environment
  and a better way to let objects go for fluent human-robot handovers. Then
  I will focus on high-level hierarchical explanation generation algorithms
  using behavior trees and finer-level references for preferred concise exp
 lanations. This includes reference production through a cognitive status-i
 nformed approach and mixed-reality robot behavior replays to reason about 
 objects no longer present. Finally\, I will discuss how augmented reality 
 can enable physically limited robots to gesture.</p>\n</div>
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