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Human-Robot Interaction
Machine Learning with Application to Robotics
Fast Adaptive Control
Dexterous Manipulation and Grasping
Computational Neuroscience and Cognitive Modeling

Fast Adaptive Control

Perfect robotic controls can never exist, so we work to devise control strategies for unexpected changes. We develop algorithms and controllers so that our robots are capable of reacting in a fast changing environment.


We develop approaches and applications:
  • allow us to coordinate the motion of the robots with external agents
  • compensate for the uncertainties in the motion of the agents and robots
  • adapting adequately and on-the-fly obstacles and sudden perturbations
  • coordinate multi-armed robotic systems to improve manipulability of a system
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    Related publications

    A. G. Billard. Towards Reproducing Humans' Exquisite Dexterity and Reactivity. 11th ACM/IEEE International Conference on Human-Robot Interaction (HRI), Christchurch, NEW ZEALAND, 2016.
    S. Kim, A. Shukla and A. Billard. Catching Objects in Flight, in IEEE Transactions on Robotics, vol. 30, num. 5, 2014.
    S. Kim, A. Billard (Dir.). Rapid and reactive robot control framework for catching objects in flight. EPFL, Lausanne, 2014.