Search Results for author:
Found 4 papers, 0 papers with code
NOD-TAMP: Multi-Step Manipulation Planning with Neural Object Descriptors
Developing intelligent robots for complex manipulation tasks in household and factory settings remains challenging due to long-horizon tasks, contact-rich manipulation, and the need to generalize across a wide variety of object shapes and scene layouts.
Human-in-the-Loop Task and Motion Planning for Imitation Learning
Finally, we collected 2. 1K demos with HITL-TAMP across 12 contact-rich, long-horizon tasks and show that the system often produces near-perfect agents.
Imitating Task and Motion Planning with Visuomotor Transformers
In this work, we show that the combination of large-scale datasets generated by TAMP supervisors and flexible Transformer models to fit them is a powerful paradigm for robot manipulation.
Cooperative Task and Motion Planning for Multi-Arm Assembly Systems
Multi-robot assembly systems are becoming increasingly appealing in manufacturing due to their ability to automatically, flexibly, and quickly construct desired structural designs.
