Robotic pick and place tasks are symmetric under translations and rotati...
Real-world grasp detection is challenging due to the stochasticity in gr...
Although equivariant machine learning has proven effective at many tasks...
Extensive work has demonstrated that equivariant neural networks can
sig...
Reinforcement learning in partially observable domains is challenging du...
In robotic manipulation, acquiring samples is extremely expensive becaus...
Given point cloud input, the problem of 6-DoF grasp pose detection is to...
We present BulletArm, a novel benchmark and learning-environment for rob...
Recently, equivariant neural network models have been shown to be useful...
Equivariant neural networks enforce symmetry within the structure of the...
In planar grasp detection, the goal is to learn a function from an image...
Transporter Net is a recently proposed framework for pick and place that...
Recently, a variety of new equivariant neural network model architecture...
In robotics, it is often not possible to learn useful policies using pur...
In the spatial action representation, the action space spans the space o...
Many people with motor disabilities struggle with activities of daily li...