233 citations · 451 across the 42 of their papers we have counts for
7 papers · 1 filter
Neural Grasp Distance Fields for Robot Manipulation
Thomas Weng, David Held, Franziska Meier +1
We formulate grasp learning as a neural field and present Neural Grasp Distance Fields (NGDF). Here, the input is a 6D pose of a robot end effector and output is a distance to a co…
MidasTouch: Monte-Carlo inference over distributions across sliding touch
Sudharshan Suresh, Zilin Si, Stuart Anderson +2
We present MidasTouch, a tactile perception system for online global localization of a vision-based touch sensor sliding on an object surface. This framework takes in posed tactile…
In-Hand Gravitational Pivoting Using Tactile Sensing
Jason Toskov, Rhys Newbury, Mustafa Mukadam +2
We study gravitational pivoting, a constrained version of in-hand manipulation, where we aim to control the rotation of an object around the grip point of a parallel gripper. To ac…
Neural Contact Fields: Tracking Extrinsic Contact with Tactile Sensing
Carolina Higuera, Siyuan Dong, Byron Boots +1
We present Neural Contact Fields, a method that brings together neural fields and tactile sensing to address the problem of tracking extrinsic contact between object and environmen…
TASKOGRAPHY: Evaluating robot task planning over large 3D scene graphs
Christopher Agia, Krishna Murthy Jatavallabhula, Mohamed Khodeir +5
3D scene graphs (3DSGs) are an emerging description; unifying symbolic, topological, and metric scene representations. However, typical 3DSGs contain hundreds of objects and symbol…
Theseus: A Library for Differentiable Nonlinear Optimization
Luis Pineda, Taosha Fan, Maurizio Monge +10
We present Theseus, an efficient application-agnostic open source library for differentiable nonlinear least squares (DNLS) optimization built on PyTorch, providing a common framew…
iSDF: Real-Time Neural Signed Distance Fields for Robot Perception
Joseph Ortiz, Alexander Clegg, Jing Dong +4
We present iSDF, a continual learning system for real-time signed distance field (SDF) reconstruction. Given a stream of posed depth images from a moving camera, it trains a random…