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 …

Articulated objects pose a unique challenge for robotic perception and manipulation. Their
increased number of degrees-of-freedom makes tasks such as localization computationally …

Robots deployed in human-centric environments may need to manipulate a diverse range of
articulated objects, such as doors, dishwashers, and cabinets. Articulated objects often …

We propose an unsupervised vision-based system to estimate the joint configurations of the
robot arm from a sequence of RGB or RGB-D images without knowing the model a priori …

Manipulating an articulated object requires perceiving its kinematic hierarchy: its parts, how
each can move, and how those motions are coupled. Previous work has explored …

In this paper, we investigate the problems that Convolutional Neural Networks (CNN)-based
pose estimators have with symmetric objects. We considered the value of the CNN's output …

Robotic manipulation of articulated objects, such as opening and closing doors, drawers,
and cabinets, appears to be an emerging research topic in robotics. This is evidenced by a …

Decentralized coordination for multi-robot systems involves planning in challenging, high-
dimensional spaces. The planning problem is particularly challenging in the presence of …

Articulated objects and their representations pose a difficult problem for robots. These
objects require not only representations of geometry and texture, but also of the various …

The dominant majority of 3D models that appear in gaming, VR/AR, and those we use to
train geometric deep learning algorithms are incomplete, since they are modeled as surface …