2 papers
cs.RO2022
Sequence-Based Plan Feasibility Prediction for Efficient Task and Motion Planning
Zhutian Yang, Caelan Reed Garrett, Tomás Lozano-Pérez +2
We present a learning-enabled Task and Motion Planning (TAMP) algorithm for solving mobile manipulation problems in environments with many articulated and movable obstacles. Our id…
cs.RO2022
Let's Handle It: Generalizable Manipulation of Articulated Objects
Zhutian Yang, Aidan Curtis
In this project we present a framework for building generalizable manipulation controller policies that map from raw input point clouds and segmentation masks to joint velocities.…