Object manipulation from 3D visual inputs poses many challenges on building generalizable
perception and policy models. However, 3D assets in existing benchmarks mostly lack the …

Human life is populated with articulated objects. A comprehensive understanding of
articulated objects, namely appearance, structure, physics property, and semantics, will …

To enable general-purpose robots, we will require the robot to operate daily articulated
objects as humans do. Current robot manipulation has heavily relied on using a parallel …

A kitchen assistant needs to operate human-scale objects, such as cabinets and ovens, in
unmapped environments with dynamic obstacles. Autonomous interactions in such …

We introduce MultiScan, a scalable RGBD dataset construction pipeline leveraging
commodity mobile devices to scan indoor scenes with articulated objects and web-based …

We present Cart, a new approach towards articulated-object manipulations by human
commands. Beyond the existing work that focuses on inferring articulation structures, we …

We address the task of predicting what parts of an object can open and how they move
when they do so. The input is a single image of an object, and as output we detect what …

Interactions with articulated objects are a challenging but important task for mobile robots.
To tackle this challenge, we propose a novel closed-loop control pipeline, which integrates …

We introduce Structure from Action (SfA), a framework to discover 3D part geometry and joint
parameters of unseen articulated objects via a sequence of inferred interactions. Our key …

Generalizable object manipulation skills are critical for intelligent and multi-functional robots
to work in real-world complex scenes. Despite the recent progress in reinforcement learning …