EI Seminar - Marc Toussaint - From Physical Reasoning to Image-based Reactive Manipulation

Our work on Task and Motion Planning (TAMP) in the last years provided
some insights on how complex manipulation problems could in principle
be tackled. However, it also raises classical questions: 1) How to
reactively control and execute robotic manipulation? 2) How to realize
physical reasoning and manipulation planning based on perception
rather than a known mesh-based scene? 3) How to leverage learning from
a model-based solver? I will discuss our team's recent research on
these questions.

Marc Toussaint is professor for Intelligent Systems at TU Berlin since
March 2020 and was Max Planck Fellow at the MPI for Intelligent Systems
2018-21. In 2017/18 he spend a year as visiting scholar
at MIT, before that some months with Amazon Robotics, and was
professor for Machine Learning and Robotics at the University of
Stuttgart since 2012. In his view, a key in understanding and
creating strongly generalizing intelligence is the integration of
learning and reasoning. His research combines AI planning,
optimization, and machine learning to tackle fundamental problems in
robotics. His work was awarded best paper at R:SS'18 and ICMLA'07, and
runner up at R:SS'12 and UAI'08.