5 citations · 8 across the 12 of their papers we have counts for
6 papers · 1 filter
SPOT: SE(3) Pose Trajectory Diffusion for Object-Centric Manipulation
Cheng-Chun Hsu, Bowen Wen, Jie Xu +5
We introduce SPOT, an object-centric imitation learning framework. The key idea is to capture each task by an object-centric representation, specifically the SE(3) object pose traj…
SkillMimicGen: Automated Demonstration Generation for Efficient Skill Learning and Deployment
Caelan Garrett, Ajay Mandlekar, Bowen Wen +1
Imitation learning from human demonstrations is an effective paradigm for robot manipulation, but acquiring large datasets is costly and resource-intensive, especially for long-hor…
FORGE: Force-Guided Exploration for Robust Contact-Rich Manipulation under Uncertainty
Michael Noseworthy, Bingjie Tang, Bowen Wen +7
We present FORGE, a method for sim-to-real transfer of force-aware manipulation policies in the presence of significant pose uncertainty. During simulation-based policy learning, F…
AutoMate: Specialist and Generalist Assembly Policies over Diverse Geometries
Bingjie Tang, Iretiayo Akinola, Jie Xu +7
Robotic assembly for high-mixture settings requires adaptivity to diverse parts and poses, which is an open challenge. Meanwhile, in other areas of robotics, large models and sim-t…
NeRFDeformer: NeRF Transformation from a Single View via 3D Scene Flows
Zhenggang Tang, Zhongzheng Ren, Xiaoming Zhao +4
We present a method for automatically modifying a NeRF representation based on a single observation of a non-rigid transformed version of the original scene. Our method defines the…
Neural Implicit Representation for Building Digital Twins of Unknown Articulated Objects
Yijia Weng, Bowen Wen, Jonathan Tremblay +4
We address the problem of building digital twins of unknown articulated objects from two RGBD scans of the object at different articulation states. We decompose the problem into tw…