5 papers
iRiSC: Iterative Risk Sensitive Control for Nonlinear Systems with Imperfect Observations
Bilal Hammoud, Armand Jordana, Ludovic Righetti
This work addresses the problem of risk-sensitive control for nonlinear systems with imperfect state observations, extending results for the linear case. In particular, we derive a…
Leveraging Forward Model Prediction Error for Learning Control
Sarah Bechtle, Bilal Hammoud, Akshara Rai +2
Learning for model based control can be sample-efficient and generalize well, however successfully learning models and controllers that represent the problem at hand can be challen…
Impedance Optimization for Uncertain Contact Interactions Through Risk Sensitive Optimal Control
Bilal Hammoud, Majid Khadiv, Ludovic Righetti
This paper addresses the problem of computing optimal impedance schedules for legged locomotion tasks involving complex contact interactions. We formulate the problem of impedance…
TriFinger: An Open-Source Robot for Learning Dexterity
Manuel Wüthrich, Felix Widmaier, Felix Grimminger +12
Dexterous object manipulation remains an open problem in robotics, despite the rapid progress in machine learning during the past decade. We argue that a hindrance is the high cost…
Crocoddyl: An Efficient and Versatile Framework for Multi-Contact Optimal Control
Carlos Mastalli, Rohan Budhiraja, Wolfgang Merkt +7
We introduce Crocoddyl (Contact RObot COntrol by Differential DYnamic Library), an open-source framework tailored for efficient multi-contact optimal control. Crocoddyl efficiently…