6 papers
B-spline Policy: Accelerating Manipulation Policies via B-spline Action Representations
Xiaoshen Han, Haoyu Xiong, Haonan Chen +4
In this work, we present B-spline Policy (BSP), an action representation designed for accelerating robot manipulation policies. Rather than predicting discrete-time action chunks,…
EgoVerse: An Egocentric Human Dataset for Robot Learning from Around the World
Ryan Punamiya, Simar Kareer, Zeyi Liu +37
Robot learning increasingly depends on large and diverse data, yet robot data collection remains expensive and difficult to scale. Egocentric human data offer a promising alternati…
OPENTOUCH: Bringing Full-Hand Touch to Real-World Interaction
Yuxin Ray Song, Jinzhou Li, Rao Fu +12
The human hand is our primary interface to the physical world, yet egocentric perception rarely knows when, where, or how forcefully it makes contact. Robust wearable tactile senso…
Vision in Action: Learning Active Perception from Human Demonstrations
Haoyu Xiong, Xiaomeng Xu, Jimmy Wu +3
We present Vision in Action (ViA), an active perception system for bimanual robot manipulation. ViA learns task-relevant active perceptual strategies (e.g., searching, tracking, an…
Bimanual Dexterity for Complex Tasks
Kenneth Shaw, Yulong Li, Jiahui Yang +5
To train generalist robot policies, machine learning methods often require a substantial amount of expert human teleoperation data. An ideal robot for humans collecting data is one…
SPIN: Simultaneous Perception, Interaction and Navigation
Shagun Uppal, Ananye Agarwal, Haoyu Xiong +2
While there has been remarkable progress recently in the fields of manipulation and locomotion, mobile manipulation remains a long-standing challenge. Compared to locomotion or sta…