Learning to Infer Kinematic Hierarchies for Novel Object Instances
Hameed Abdul-Rashid,Miles Freeman,Ben Abbatematteo,George Konidaris,Daniel Ritchie,Hameed Abdul-Rashid,Miles Freeman,Ben Abbatematteo,George Konidaris,Daniel Ritchie
Manipulating an articulated object requires perceiving its kinematic hierarchy: its parts, how each can move, and how those motions are coupled. Previous work has explored perception for kinematics, but none infers a complete kinematic hierarchy on never-before-seen object instances, without relying on a schema or template. We present a novel perception system that achieves this goal. Our system i...
