(r2) Ziebart - IOCRLfD
Robot learning from demonstration Inverse Optimal Control & Robotic Learning from Demonstration

A proposed workshop in conjunction with Robotics: Science and Systems 2013. In many robotic domains, it is much easier to demonstrate appropriate behavior (through e.g., tele-operation, haptic feedback, or motion capture) than it is to program a controller to produce the same behavior. Human (and animal) brains are equipped with mirror neurons that are believed to provide this key cognitive capability. Driven by these observations, research in learning from demonstration and inverse optimal control has become increasingly popular in the last several years. This paradigm recasts reinforcement learning problems as supervised learning tasks, in which advances in machine learning can enable robots to learn the desired policy, utility, and/or dynamics of the robotic domain directly and efficiently from observed behavior. For example, inverse optimal control aims at identifying the unknown objective function or policy that produces a given solution of an optimal control problem. Input data can come from measurements related to the system’s state e.g. by motion capture, IMU or force plates. The identified function can then be used to generate optimal motions for robots. An important goal of this workshop is to present and discuss the state of the art of solution methods for this challenging class of problems.

In this workshop, via a mix of invited talks, posters, and discussion, we seek to bring together experts in system identification, reinforcement learning, and inverse optimal control to explore the theoretical and applied aspects of learning from demonstration and inverse optimal control. We plan to discuss open problems, state-of-the-art solution methods, and interesting applications.

Call for papers: forthcoming

Preliminary Schedule:
08:00 - 09:00 morning coffee
09:00 - 10:30 Three invited talks (programming from demonstration)

10:30 - 11:00 coffee break
11:00 - 12:30 Three invited talks (inverse optimal control)
12:30 - 14:00 lunch break
14:00 - 15:30 Three invited talks (applications & algorithms)
15:30 - 16:00 coffee break (poster set-up)
16:00 - 17:00 poster session
17:00 - 17:30 discussion

Workshop Organizers:

  • Byron Boots, University of Washington
  • Tim Bretl, University of Illinois at Urbana-Champaign
  • Katja Mombaur, Ruprecht-Karls-Universitšt Heidelberg
  • Brian Ziebart, University of Illinois at Chicago
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