1 citations · 1 across the 4 of their papers we have counts for
4 papers
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…
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…
SEIL: Simulation-augmented Equivariant Imitation Learning
Mingxi Jia, Dian Wang, Guanang Su +4
In robotic manipulation, acquiring samples is extremely expensive because it often requires interacting with the real world. Traditional image-level data augmentation has shown the…
Sample Efficient Grasp Learning Using Equivariant Models
Xupeng Zhu, Dian Wang, Ondrej Biza +3
In planar grasp detection, the goal is to learn a function from an image of a scene onto a set of feasible grasp poses in . In this paper, we recognize that the opt…