18
Jun
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
Related
Munich AI Lectures • 22.07.2024 • TUM Garching Campus, FMI Building, Hörsaal 2 (00.04.011), Boltzmannstr. 3, 85748 Garching bei München or online via Livestream
Multi-Modal and Multi-Robot Coordination in Challenging Environments
Munich AI Lecture with Sebastian Scherer from CMU outlining some of their approaches progress, and results on multi-modal sensing.
Munich AI Lectures • 17.07.2024 • Bayerische Akademie der Wissenschaften, Plenarsaal, 1. Stock, Alfons-Goppel-Straße 11, 80539 München
We are (still?) not giving data enough credit
Munich AI Highlight Lecture with Alexei A. Efros from UC Berkeley, emphasizing the critical role of data in Computer Vision with historical examples and recent work.
Munich AI Lectures • 15.07.2024 • TU Munich, Institute for Advanced Study, Auditorium (Ground floor), Lichtenbergstraße 2a, 85748 Garching
Physical AI: Promises and Challenges
Munich AI Lecture with Daniela Rus from MIT discussing recent developments in ML and robotics.
Munich AI Lectures • 25.06.2024 • TUM Campus Munich, Room 0790, Arcisstraße 21, 80333 München
From Video Understanding to Embodied Agents
The MCML invites you to the Munich AI Lectures with Ivan Laptev discussing AI models that make reliable predictions from explanatory videos.
Munich AI Lectures • 08.04.2024 • TUM, Arcisstr. 21, 80333 Munich, Room 0790 (ground floor)
Learning complex robotic behaviors with optimal control
Munich AI Lecture with Marc Toussaint from TU Berlin taking a look at the progress and prospects of AI in robotics.