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Motion Tracks: A Unified Representation for Human-Robot Transfer in Few-Shot Imitation Learning
Teaching robots to autonomously complete everyday tasks remains a challenge. Imitation
Learning (IL) is a powerful approach that imbues robots with skills via demonstrations, but is …
Learning (IL) is a powerful approach that imbues robots with skills via demonstrations, but is …
SPOT: SE (3) Pose Trajectory Diffusion for Object-Centric Manipulation
We introduce SPOT, an object-centric imitation learning framework. The key idea is to
capture each task by an object-centric representation, specifically the SE (3) object pose …
capture each task by an object-centric representation, specifically the SE (3) object pose …
Robot Data Curation with Mutual Information Estimators
The performance of imitation learning policies often hinges on the datasets with which they
are trained. Consequently, investment in data collection for robotics has grown across both …
are trained. Consequently, investment in data collection for robotics has grown across both …
STRAP: Robot Sub-Trajectory Retrieval for Augmented Policy Learning
Robot learning is witnessing a significant increase in the size, diversity, and complexity of
pre-collected datasets, mirroring trends in domains such as natural language processing …
pre-collected datasets, mirroring trends in domains such as natural language processing …
Skills Made to Order: Efficient Acquisition of Robot Cooking Skills Guided by Multiple Forms of Internet Data
This study explores the utility of various internet data sources to select among a set of
template robot behaviors to perform skills. Learning contact-rich skills involving tool use from …
template robot behaviors to perform skills. Learning contact-rich skills involving tool use from …