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cs.RO2025
Using Temperature Sampling to Effectively Train Robot Learning Policies on Imbalanced Datasets
Basavasagar Patil, Sydney Belt, Jayjun Lee +2
Increasingly large datasets of robot actions and sensory observations are being collected to train ever-larger neural networks. These datasets are collected based on tasks and whil…
cs.RO2025
AimBot: A Simple Auxiliary Visual Cue to Enhance Spatial Awareness of Visuomotor Policies
Yinpei Dai, Jayjun Lee, Yichi Zhang +6
In this paper, we propose AimBot, a lightweight visual augmentation technique that provides explicit spatial cues to improve visuomotor policy learning in robotic manipulation. Aim…
cs.RO2025
ViTaSCOPE: Visuo-tactile Implicit Representation for In-hand Pose and Extrinsic Contact Estimation
Jayjun Lee, Nima Fazeli
Mastering dexterous, contact-rich object manipulation demands precise estimation of both in-hand object poses and external contact locations$\unicode{x2013}$tasks particularly chal…