The Helping Hands Lab

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

(2024). Fourier Transporter: Bi-Equivariant Robotic Manipulation in 3D. In ICLR 2023.

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Fourier Transporter: Bi-Equivariant Robotic Manipulation in 3D
(2023). Leveraging Pick and Place Symmetries. In IJRR 2023.

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Leveraging Pick and Place Symmetries
(2023). A General Theory of Correct, Incorrect, and Extrinsic Equivariance. In NeurIPS 2023.

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A General Theory of Correct, Incorrect, and Extrinsic Equivariance
(2023). Invariant Slot Attention: Object Discovery with Slot-Centric Reference Frames. In ICML'23.

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Invariant Slot Attention: Object Discovery with Slot-Centric Reference Frames
(2023). One-shot Imitation Learning via Interaction Warping. In CoRL'23.

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One-shot Imitation Learning via Interaction Warping
(2023). Equivariant Reinforcement Learning under Partial Observability. In CoRL 2023.

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Equivariant Reinforcement Learning under Partial Observability
(2023). On robot grasp learning using equivariant models. In Autonomous Robots.

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On robot grasp learning using equivariant models
(2023). The Surprising Effectiveness of Equivariant Models in Domains with Latent Symmetry. In ICLR 2023.

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The Surprising Effectiveness of Equivariant Models in Domains with Latent Symmetry
(2023). Image to Sphere: Learning Equivariant Features for Efficient Pose Prediction. In ICLR'23.

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Image to Sphere: Learning Equivariant Features for Efficient Pose Prediction
(2023). SEIL: Simulation-augmented Equivariant Imitation Learning. In ICRA 2023.

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SEIL: Simulation-augmented Equivariant Imitation Learning