2 citations · 2 across the 14 of their papers we have counts for
29 papers · 1 filter
Enhancing Visual Domain Robustness in Behaviour Cloning via Saliency-Guided Augmentation
Zheyu Zhuang, Ruiyu Wang, Nils Ingelhag +2
In vision-based behavior cloning (BC), conventional image augmentations such as Random Crop and Color Jitter often fall short under substantial visual domain shifts, including chan…
On the Generalization Capabilities, Design Choices and Limitations of Keypoint Imitation Learning
Thomas Lips, Marco Moletta, Michael C. Welle +2
RGB-based imitation learning requires many demonstrations to generalize to unseen objects or scenes, motivating research into intermediate representations to improve generalization…
Real-Time Operator Takeover for Visuomotor Diffusion Policy Training
Marco Moletta, Michael C. Welle, Nils Ingelhag +2
We present a Real-Time Operator Takeover (RTOT) paradigm that enables operators to seamlessly take control of a live visuomotor diffusion policy, guiding the system back to desirab…
Preference Aligned Visuomotor Diffusion Policies for Deformable Object Manipulation
Marco Moletta, Michael C. Welle, Danica Kragic
Humans naturally develop preferences for how manipulation tasks should be performed, which are often subtle, personal, and difficult to articulate. Although it is important for rob…
Reduced-order Control and Geometric Structure of Learned Lagrangian Latent Dynamics
Katharina Friedl, Noémie Jaquier, Seungyeon Kim +2
Model-based controllers can offer strong guarantees on stability and convergence by relying on physically accurate dynamic models. However, these are rarely available for high-dime…
PALM: Enhanced Generalizability for Local Visuomotor Policies via Perception Alignment
Ruiyu Wang, Zheyu Zhuang, Danica Kragic +1
Generalizing beyond the training domain in image-based behavior cloning remains challenging. Existing methods address individual axes of generalization, workspace shifts, viewpoint…