24 citations · 24 across the 1 of their papers we have counts for
3 papers
cs.RO2018
SPNets: Differentiable Fluid Dynamics for Deep Neural Networks
Connor Schenck, Dieter Fox
In this paper we introduce Smooth Particle Networks (SPNets), a framework for integrating fluid dynamics with deep networks. SPNets adds two new layers to the neural network toolbo…
cs.RO2017★ 24 cited
Learning Robotic Manipulation of Granular Media
Connor Schenck, Jonathan Tompson, Dieter Fox +1
In this paper, we examine the problem of robotic manipulation of granular media. We evaluate multiple predictive models used to infer the dynamics of scooping and dumping actions.…
cs.CV2016
Detection and Tracking of Liquids with Fully Convolutional Networks
Connor Schenck, Dieter Fox
Recent advances in AI and robotics have claimed many incredible results with deep learning, yet no work to date has applied deep learning to the problem of liquid perception and re…