31 citations · 103 across the 16 of their papers we have counts for
18 papers
Fast-Grasp'D: Dexterous Multi-finger Grasp Generation Through Differentiable Simulation
Dylan Turpin, Tao Zhong, Shutong Zhang +8
Multi-finger grasping relies on high quality training data, which is hard to obtain: human data is hard to transfer and synthetic data relies on simplifying assumptions that reduce…
Grasp'D: Differentiable Contact-rich Grasp Synthesis for Multi-fingered Hands
Dylan Turpin, Liquan Wang, Eric Heiden +5
The study of hand-object interaction requires generating viable grasp poses for high-dimensional multi-finger models, often relying on analytic grasp synthesis which tends to produ…
DiSECt: A Differentiable Simulator for Parameter Inference and Control in Robotic Cutting
Eric Heiden, Miles Macklin, Yashraj Narang +3
Robotic cutting of soft materials is critical for applications such as food processing, household automation, and surgical manipulation. As in other areas of robotics, simulators c…
Inferring Articulated Rigid Body Dynamics from RGBD Video
Eric Heiden, Ziang Liu, Vibhav Vineet +2
Being able to reproduce physical phenomena ranging from light interaction to contact mechanics, simulators are becoming increasingly useful in more and more application domains whe…
Probabilistic Inference of Simulation Parameters via Parallel Differentiable Simulation
Eric Heiden, Christopher E. Denniston, David Millard +2
To accurately reproduce measurements from the real world, simulators need to have an adequate model of the physical system and require the parameters of the model be identified. We…
DiSECt: A Differentiable Simulation Engine for Autonomous Robotic Cutting
Eric Heiden, Miles Macklin, Yashraj Narang +3
Robotic cutting of soft materials is critical for applications such as food processing, household automation, and surgical manipulation. As in other areas of robotics, simulators c…