47 citations · 142 across the 49 of their papers we have counts for
11 papers · 1 filter
Simultaneous Extrinsic Contact and In-Hand Pose Estimation via Distributed Tactile Sensing
Mark Van der Merwe, Kei Ota, Dmitry Berenson +2
Prehensile autonomous manipulation, such as peg insertion, tool use, or assembly, require precise in-hand understanding of the object pose and the extrinsic contacts made during in…
GrOMP: Grasped Object Manifold Projection for Multimodal Imitation Learning of Manipulation
William van den Bogert, Gregory Linkowski, Nima Fazeli
Imitation Learning (IL) holds great potential for learning repetitive manipulation tasks, such as those in industrial assembly. However, its effectiveness is often limited by insuf…
Learning Diffusion Policies for Robotic Manipulation of Timber Joinery under Fabrication Uncertainty
Salma Mozaffari, Daniel Ruan, William van den Bogert +3
Fabrication uncertainty arising from tolerance accumulation, material imperfection, and positioning errors remains a critical barrier to automated robotic assembly in construction,…
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…
Cross-Sensor Touch Generation
Samanta Rodriguez, Yiming Dou, Miquel Oller +2
Today's visuo-tactile sensors come in many shapes and sizes, making it challenging to develop general-purpose tactile representations. This is because most models are tied to a spe…
Hydrosoft: Non-Holonomic Hydroelastic Models for Compliant Tactile Manipulation
Miquel Oller, An Dang, Nima Fazeli
Tactile sensors have long been valued for their perceptual capabilities, offering rich insights into the otherwise hidden interface between the robot and grasped objects. Yet their…
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…
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…
Vib2Move: In-Hand Object Reconfiguration via Fingertip Micro-Vibrations
Xili Yi, Nima Fazeli
We introduce Vib2Move, a novel approach for in-hand object reconfiguration that uses fingertip micro-vibrations and gravity to precisely reposition planar objects. Our framework co…
Estimating Deformable-Rigid Contact Interactions for a Deformable Tool via Learning and Model-Based Optimization
Mark Van der Merwe, Miquel Oller, Dmitry Berenson +1
Dexterous manipulation requires careful reasoning over extrinsic contacts. The prevalence of deforming tools in human environments, the use of deformable sensors, and the increasin…
ViSA-Flow: Accelerating Robot Skill Learning via Large-Scale Video Semantic Action Flow
Changhe Chen, Quantao Yang, Xiaohao Xu +2
One of the central challenges preventing robots from acquiring complex manipulation skills is the prohibitive cost of collecting large-scale robot demonstrations. In contrast, huma…