18
Jun
Munich AI Lectures
Learning complex robotic behaviors with optimal control
Ludovic Righetti, New York University (NYU)
18.06.2024
5:00 pm - 6:00 pm
TUM, Arcisstr. 21, 80333 Munich, Room 0790 (ground floor)
On behalf of our partners at the Bavarian AI network baiosphere, the MCML cordially invites you to the Munich AI Lectures.
Nonlinear model predictive control (MPC) is effective for generating diverse robotic behaviors but faces limitations with integrating multi-modal sensing and optimizing complex, real-time behaviors.
In his talk, Ludovic Righetti from NYU will explore unifying learning and numerical optimal control to address these challenges, emphasizing the integration of machine learning with online optimization and discussing the societal impacts of robotics research.
Organized by:
baiosphere
Bavarian Academy of Science and Humanities
Helmholtz Munich
LMU Munich
TUM
AI-HUB LMU
ELLIS Munich Unit
Konrad Zuse School of Excellence in Reliable AI
MCML
Munich Data Science Institute TUM
Munich Institute of Robotics and Machine Intelligence TUM
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