In robotic tasks, changes in reference frames typically do not influence...
Real-world grasp detection is challenging due to the stochasticity in gr...
Although equivariant machine learning has proven effective at many tasks...
In robotic manipulation, acquiring samples is extremely expensive becaus...
Given point cloud input, the problem of 6-DoF grasp pose detection is to...
We study how group symmetry helps improve data efficiency and generaliza...
We present BulletArm, a novel benchmark and learning-environment for rob...
Recently, equivariant neural network models have been shown to be useful...
In planar grasp detection, the goal is to learn a function from an image...
Recently, a variety of new equivariant neural network model architecture...