The Helping Hands Lab
@Northeastern University
The Helping Hands Lab develops perception, planning, and control algorithms for robot manipulation in unstructured environments. We are particularly interested in robots that work with humans in built-for-human environments.
Publications
(2023).
Image to Sphere: Learning Equivariant Features for Efficient Pose Prediction.
In ICLR'23.
(2023).
A General Theory of Correct, Incorrect, and Extrinsic Equivariance.
In Preprint.
(2023).
SEIL: Simulation-augmented Equivariant Imitation Learning.
In ICRA 2023.
(2022).
On-Robot Learning With Equivariant Models.
In CoRL 2022.
(2022).
Grasp Learning: Models, Methods, and Performance.
In Annual Review of Control, Robotics, and Autonomous Systems, Vol 6.
(2022).
Leveraging Fully Observable Policies for Learning under Partial Observability.
In CoRL 2022.
