supported by
the STIFF
EC project
STIFF/VIACTORS Summer School on Impedance supported by
the VIACTORS
EC project
.



Keynote speakers:
Alin Albu-Schäffer, DLR
Antonio Bicchi, U. Pisa
Etienne Burdet, Imperial
Neville Hogan, MIT
Oussama Khatib, Stanford
Gerald Loeb, USC
Joseph McIntyre, UPD-CNRS
Patrick van der Smagt, DLR
Sethu Vijayakumar, Edinburgh

Sethu Vijayakumar
Director
Institute of Perception, Action & Behavior

University of Edinburgh
1.28 Informatics Forum, 10 Crichton Street
Edinburgh EH8 9AB, UK
Phone: +44 131 651 3444
sethu.vijayakumar(at)ed.ac.uk

Kloster

video part 1
view at youtube or download video

video part 2
view at youtube or download video

Sethu Vijayakumar

Designing Variable Impedance Policies: A Novel Framework

Recent advances in VIA design has equipped prototype robots with the ability to change their stiffness and damping during task execution. How can we maximally exploit this capability? In this talk, I will look at impedance modulation in three different classes of movements: point-to-point tasks like reaching, explosive movement tasks like throwing and rhythmic movement tasks such as walking. I will describe an optimal control based formulation of optimizing both the temporal profile of movement and impedance modulation in a way that is tuned to the dynamics of the plant. Several hardware tests will serve to highlight the benefits. Further, I will illustrates the pitfalls of naively mimicking impedance profiles across heterogeneous systems (e.g., human limb to VS joints or MACCEPA actuators) and describe a framework that is capable of abstracting out the specific plant dynamics while ensuring task optimality. This talk will draw upon concepts of optimal feedback control, apprenticeship learning and model free reinforcement learning besides fundamentals of dynamics representation and learning.


Note: all PDF downloads for personal use only!

Related publications

  1. Mitrovic D, Klanke S, Vijayakumar S (2011). Learning impedance control of antagonistic systems based on stochastic optimisation principles. International Journal of Robotic Research [doi]

  2. Rawlik K, Toussaint M, Vijayakumar S (2010). An Approximate Inference Approach to Temporal Optimization in Optimal Control. Proc. Advances in Neural Information Processing Systems [www]

  3. Mitrovic D, Klanke S, Osu R, Kawato M, Vijayakumar S (2010). Computational Model of Limb Impedance Control based on Principles of Internal Model Uncertainty. PLoS ONE 5 (10), [doi] [www]

  4. Howard M, Mitrovic D, Vijayakumar S (2010). Transferring Impedance Control Strategies Between Heterogeneous Systems via Apprenticeship Learning. Proc. 2010 IEEE-RAS International Conference on Humanoid Robots [www]

  5. Mitrovic D, Klanke S, Vijayakumar S (2010). Adaptive Optimal Feedback Control with Learned Internal Dynamics Models. From Motor Learning to Interaction Learning in Robots [www]