1 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.RO2023
PRIMP: PRobabilistically-Informed Motion Primitives for Efficient Affordance Learning from Demonstration
Sipu Ruan, Weixiao Liu, Xiaoli Wang +2
This paper proposes a learning-from-demonstration method using probability densities on the workspaces of robot manipulators. The method, named "PRobabilistically-Informed Motion P…
cs.RO2023★ 1 cited
Learning-Free Grasping of Unknown Objects Using Hidden Superquadrics
Yuwei Wu, Weixiao Liu, Zhiyang Liu +1
Robotic grasping is an essential and fundamental task and has been studied extensively over the past several decades. Traditional work analyzes physical models of the objects and c…
cs.CV2023★ 1 cited
Marching-Primitives: Shape Abstraction from Signed Distance Function
Weixiao Liu, Yuwei Wu, Sipu Ruan +1
Representing complex objects with basic geometric primitives has long been a topic in computer vision. Primitive-based representations have the merits of compactness and computatio…