8 papers
Wasserstein Filtering: A Sample Selection Method for Robust Distribution Learning
Yikai Xu, Zhao Chen, Jian Huang
Given a dataset where a portion of the samples are contaminated, our goal is to recover the underlying clean population distribution. To this end, we propose Wasserstein Filtering…
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…
MirrorDuo: Reflection-Consistent Visuomotor Learning from Mirrored Demonstration Pairs
Zheyu Zhuang, Ruiyu Wang, Giovanni Luca Marchetti +2
Image-based behaviour cloning leverages demonstrations captured from ubiquitous RGB cameras. However, it remains constrained by the cost of collecting diverse demos, especially for…
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…
R900: Understanding the Cost-Effectiveness of Random Exploration from 900 Hours of Robotic Data Collection
Shutong Jin, Axel Kaliff, Ruiyu Wang +2
Data scarcity presents a key bottleneck for imitation learning in robotic manipulation. In this paper, we focus on random exploration data-actions and video sequences produced auto…
Feature Extractor or Decision Maker: Rethinking the Role of Visual Encoders in Visuomotor Policies
Ruiyu Wang, Zheyu Zhuang, Shutong Jin +3
An end-to-end (E2E) visuomotor policy is typically treated as a unified whole, but recent approaches using out-of-domain (OOD) data to pretrain the visual encoder have cleanly sepa…