Morning Schedule:
- 8:45 to 9:00 am - Welcome and introduction to the workshop
- 9:00 to 9:30 am - Farbod Farshidian (Postdoctoral Research Assistant at ETH Zurich, Switzerland): A model predictive control approach for motion planning and control of legged systems
- 9:30 to 10:00 am - Robin Deits (Robotic Scientist at Boston Dynamics, USA): Learning controllers from offline global optimization by sampling value function intervals
- 10:00 to 10:30 am - Coffee break
- 10:30 to 11:00 am - Katja Mombaur (Full Professor at Heidelberg University, Germany): Combining optimal control and learning for bio-inspired motion generation for humanoid robots
- 11:00 to 11:30 am - Matteo Bianchi (Assistant Professor at Research Center "E. Piaggio", University of Pisa, Italy): A data-driven approach to autonomous grasping and reflex grasping with soft hands: combining deep learning, multi-modal minimalistic sensing, embodied intelligence and human inspiration
- 11:30 to 12:00 am - Kris Hauser (Associate Professor at Duke University, USA): Learning from optimal trajectory databases for control of nonlinear systems
- 12:00 to 12:30 am - Manolo Garabini (Assistant Professor at Research Center "E. Piaggio", University of Pisa, Italy): Optimal planning and control for soft robots
Afternoon Schedule:
- 1:30 to 2:00 pm - Gabriele Buondonno (Postdoctoral Research Assistant at LAAS-CNRS, France): Latest advances in passive walking and memory of motion
- 2:00 to 2:30 pm - Francesco Nori (Head of Robotics at Deepmind, UK): An overview of Research and Robotics at Deepmind: learning in sim and transferring to the real world
- 2:30 to 3:00 pm - Francois Hogan (PhD Candidate at Massachusetts Institute of Technology): Controlling contact interactions: From model-based planning to tactile-based control
- 3:00 to 3:30 pm - Coffee break
- 3:30 to 4:00 pm - Matei Ciocarlie (Associate Professor at Columbia University, USA): Modeling contact with Coulomb friction and the maximum dissipation principle
- 4:00 to 4:30 pm - Tobia Marcucci (PhD Candidate at Massachusetts Institute of Technology): Control through contacts via approximate explicit model predictive control
- 4:30 to 5:30 pm - Final discussion