الباحثون

Yichao Liang

المنشورات 2

نسخة أولية وصول مفتوح

EMPIRIC: Experiment-Driven Learning of Residual World Models for Robot Planning

Yichao Liang, Amber Li, Dat Nguyen وآخرون · 2026

A robot should be able to learn through experiments how unfamiliar objects behave and interact, then plan with that knowledge. It need not start from scratch: physics engines supply knowledge of motion and contact, but can omit entire mechanisms, such as glue curing, water heating, or wind. We present EMPIRIC, an agent …

نسخة أولية وصول مفتوح

Coding Agents for Generalized Task and Motion Planning Problems

Matteo Merler, Bowen Li, Josh Roy وآخرون · 2026

Task and motion planning (TAMP) problems remain difficult even with full observability and object-centric states because discrete decisions are tightly coupled to geometric, kinematic, and dynamic constraints. Generalized TAMP addresses this difficulty by exploiting regularities across problem instances to reduce plann …

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