100 citations · 399 across the 42 of their papers we have counts for
51 papers
Symmetric Models for Visual Force Policy Learning
Colin Kohler, Anuj Shrivatsav Srikanth, Eshan Arora +1
While it is generally acknowledged that force feedback is beneficial to robotic control, applications of policy learning to robotic manipulation typically only leverage visual feed…
Leveraging Symmetries in Pick and Place
Haojie Huang, Dian Wang, Arsh Tangri +2
Robotic pick and place tasks are symmetric under translations and rotations of both the object to be picked and the desired place pose. For example, if the pick object is rotated o…
On Robot Grasp Learning Using Equivariant Models
Xupeng Zhu, Dian Wang, Guanang Su +3
Real-world grasp detection is challenging due to the stochasticity in grasp dynamics and the noise in hardware. Ideally, the system would adapt to the real world by training direct…
One-shot Imitation Learning via Interaction Warping
Ondrej Biza, Skye Thompson, Kishore Reddy Pagidi +7
Imitation learning of robot policies from few demonstrations is crucial in open-ended applications. We propose a new method, Interaction Warping, for learning SE(3) robotic manipul…
A General Theory of Correct, Incorrect, and Extrinsic Equivariance
Dian Wang, Xupeng Zhu, Jung Yeon Park +4
Although equivariant machine learning has proven effective at many tasks, success depends heavily on the assumption that the ground truth function is symmetric over the entire doma…
Image to Sphere: Learning Equivariant Features for Efficient Pose Prediction
David M. Klee, Ondrej Biza, Robert Platt +1
Predicting the pose of objects from a single image is an important but difficult computer vision problem. Methods that predict a single point estimate do not predict the pose of ob…