From the 1 of 3 linked papers with an AI index.
3 papers
cs.RO2026
PokeNet: Learning Kinematic Models of Articulated Objects from Human Observations
Anmol Gupta, Weiwei Gu, Omkar Patil +2
PokeNet is an end-to-end system that learns the kinematic models of unknown articulated objects from a single human demonstration, predicting joint parameters, manipulation order,…
cs.RO2026
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…
cs.RO2025
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…