4 papers · 1 filter
PokeNet: Learning Kinematic Models of Articulated Objects from Human Observations
Anmol Gupta, Weiwei Gu, Omkar Patil +2
Articulation modeling enables robots to learn joint parameters of articulated objects for effective manipulation which can then be used downstream for skill learning or planning. E…
Learning Sequential Kinematic Models from Demonstrations for Multi-Jointed Articulated Objects
Anmol Gupta, Weiwei Gu, Omkar Patil +2
As robots become more generalized and deployed in diverse environments, they must interact with complex objects, many with multiple independent joints or degrees of freedom (DoF) r…
Continual Robot Skill and Task Learning via Dialogue
Weiwei Gu, Suresh Kondepudi, Anmol Gupta +2
Interactive robot learning is a challenging problem as the robot is present with human users who expect the robot to learn novel skills to solve novel tasks perpetually with sample…
Interactive Visual Task Learning for Robots
Weiwei Gu, Anant Sah, Nakul Gopalan
We present a framework for robots to learn novel visual concepts and tasks via in-situ linguistic interactions with human users. Previous approaches have either used large pre-trai…