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DTSTART:20251026T030000
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UID:calendar.30675.field_data.0@www.diag.uniroma1.it
DTSTAMP:20260429T141622Z
CREATED:20260427T115143Z
DESCRIPTION:Abstract:Embodied intelligence lies at the intersection where a
 rtificial intelligence meets physical bodies\, and is vividly exemplified 
 by recent advances in mobile robotics enabled by high-performance percepti
 on sensors and actuators. For dynamic state estimation using multimodal se
 nsors\, we explore methodologies based on continuous-time motion represent
 ation\, particularly using B-splines and Gaussian processes. These methods
  have been validated in a variety of real-world settings for localization\
 , odometry\, and mapping\, involving sensors such as IMU\, LiDAR\, UWB\, a
 nd camera\, and have been deployed on wheeled\, legged\, wearable\, and ae
 rial platforms. Furthermore\, we introduce sim-to-real reinforcement learn
 ing approaches toward achieving motor intelligence in legged locomotion. B
 uilding on this foundation\, we demonstrate possible ways to incorporate p
 erceptive inputs\, enabling robots to navigate through dynamic and unstruc
 tured environments. The talk aims to provide balanced insights from both m
 ethodological and engineering perspectives\, with an emphasis on real-worl
 d\, real-time challenges. Short bio:Kailai Li is an Assistant Professor wi
 th tenure at the University of Groningen\, The Netherlands. He earned his 
 B.E. in Mechanical Engineering and Automation from Tsinghua University\, h
 is M.Sc. in Automation Engineering from RWTH Aachen University\, including
  a master’s thesis at ETH Zurich\, and his Ph.D. from the Karlsruhe Instit
 ute of Technology (KIT)\, Germany. He now leads the Agile Sensing and Inte
 lligence Group (ASIG) with focuses on building future-proof embodied AI sy
 stems for the real world. The group’s research spans sensing to actuation 
 with open-source contributions (GitHub: https://github.com/ASIG-X). 
DTSTART;TZID=Europe/Paris:20260429T143000
DTEND;TZID=Europe/Paris:20260429T143000
LAST-MODIFIED:20260427T122320Z
LOCATION:Aula Magna
SUMMARY:On Continuous-Time State Estimation for Mobile Robotic Systems. Sem
 inario prof. Kailai Li -
URL;TYPE=URI:https://www.diag.uniroma1.it/node/30675
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