activity
20102019
most citedConnecting Touch and Vision via Cross-Modal Prediction

10 citations · 25 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV201910 cited

Connecting Touch and Vision via Cross-Modal Prediction

Yunzhu Li, Jun-Yan Zhu, Russ Tedrake +1

Humans perceive the world using multi-modal sensory inputs such as vision, audition, and touch. In this work, we investigate the cross-modal connection between vision and touch. Th…

cs.CV20195 cited

SurfelWarp: Efficient Non-Volumetric Single View Dynamic Reconstruction

Wei Gao, Russ Tedrake

We contribute a dense SLAM system that takes a live stream of depth images as input and reconstructs non-rigid deforming scenes in real time, without templates or prior models. In…

cs.RO2017

Functional Co-Optimization of Articulated Robots

Andrew Spielberg, Brandon Araki, Cynthia Sung +2

We present parametric trajectory optimization, a method for simultaneously computing physical parameters, actuation requirements, and robot motions for more efficient robot designs…

cs.CV20179 cited

LabelFusion: A Pipeline for Generating Ground Truth Labels for Real RGBD Data of Cluttered Scenes

Pat Marion, Peter R. Florence, Lucas Manuelli +1

Deep neural network (DNN) architectures have been shown to outperform traditional pipelines for object segmentation and pose estimation using RGBD data, but the performance of thes…

math.DS20101 cited

Invariant Funnels around Trajectories using Sum-of-Squares Programming

Mark M. Tobenkin, Ian R. Manchester, Russ Tedrake

This paper presents numerical methods for computing regions of finite-time invariance (funnels) around solutions of polynomial differential equations. First, we present a method wh…