Search Results for author:
Found 6 papers, 3 papers with code
Model-free Reinforcement Learning for Robust Locomotion using Demonstrations from Trajectory Optimization
We present a general, two-stage reinforcement learning approach to create robust policies that can be deployed on real robots without any additional training using a single demonstration generated by trajectory optimization.
Robot Learning with Crash Constraints
We consider failing behaviors as those that violate a constraint and address the problem of learning with crash constraints, where no data is obtained upon constraint violation.
Robust walking based on MPC with viability guarantees
In this approach, instead of adding a (conservative) terminal constraint to the problem, we propose to use the measured state projected to the viability kernel in the OCP solved at each control cycle.
Robotics
TriFinger: An Open-Source Robot for Learning Dexterity
Dexterous object manipulation remains an open problem in robotics, despite the rapid progress in machine learning during the past decade.
An Open Torque-Controlled Modular Robot Architecture for Legged Locomotion Research
Finally, to demonstrate the capabilities of the quadruped, we present a novel controller which combines feedforward contact forces computed from a kino-dynamic optimizer with impedance control of the center of mass and base orientation.
Robotics
Learning Variable Impedance Control for Contact Sensitive Tasks
We propose learning a policy giving as output impedance and desired position in joint space and compare the performance of that approach to torque and position control under different contact uncertainties.
