Diagrammatic Teaching is a paradigm for robots to acquire novel skills,
...
Robots should exist anywhere humans do: indoors, outdoors, and even unma...
Learning for Demonstration (LfD) enables robots to acquire new skills by...
Most real-world 3D measurements from depth sensors are incomplete, and t...
Underwater imagery often exhibits distorted coloration as a result of
li...
LiDARs have been widely adopted to modern self-driving vehicles, providi...
Recent advances in neural radiance fields (NeRFs) achieve state-of-the-a...
In this report, we present the system design, operational strategy, and
...
This paper presents a novel visual scene mapping method for underwater
v...
Robot localization remains a challenging task in GPS denied environments...
Accurate prediction of pedestrian crossing behaviors by autonomous vehic...
Highway driving invariably combines high speeds with the need to interac...
Point cloud analysis is an area of increasing interest due to the develo...
Pedestrian trajectory prediction is an essential task in robotic applica...
The continual improvement of 3D sensors has driven the development of
al...
Uncooled microbolometers can enable robots to see in the absence of visi...
Pedestrians and drivers interact closely in a wide range of environments...
The design of optical systems for underwater vehicles is a complex proce...
There has been much recent interest in deep learning methods for monocul...
For robotic arms to operate in arbitrary environments, especially near
p...
Online control design using a high-fidelity, full-order model for a bipe...
Illumination effects in images, specifically cast shadows and shading, h...
Knowing and predicting dangerous factors within a scene are two key
comp...
Highway driving places significant demands on human drivers and autonomo...
An accurate depth map of the environment is critical to the safe operati...
Urban environments pose a significant challenge for autonomous vehicles ...
As autonomous robots increasingly become part of daily life, they will o...
This paper presents an interconnected control-planning strategy for redu...
Autonomous robot manipulation often involves both estimating the pose of...
Autonomous mobile robots must operate with limited sensor horizons in
un...
Performance on benchmark datasets has drastically improved with advances...
Recent work has shown that convolutional neural networks (CNNs) can be
a...
Navigating safely in urban environments remains a challenging problem fo...
In applications such as autonomous driving, it is important to understan...
This paper presents a novel dataset titled PedX, a large-scale multimoda...
Recent work has focused on generating synthetic imagery and augmenting r...
Constructing a spatial map of environmental parameters is a crucial step...
One of the major open challenges in self-driving cars is the ability to
...
This paper reports on WaterGAN, a generative adversarial network (GAN) f...
Deep learning has rapidly transformed the state of the art algorithms us...