Current state-of-the-art methods for panoptic segmentation require an im...
Localization is paramount for autonomous robots. While camera and LiDAR-...
Most automated driving systems comprise a diverse sensor set, including
...
Maps have played an indispensable role in enabling safe and automated
dr...
Unlike humans, who can effortlessly estimate the entirety of objects eve...
In today's chemical production plants, human field operators perform fre...
Safety and efficiency are paramount in healthcare facilities where the l...
Existing object-search approaches enable robots to search through free
p...
Autonomous driving involves complex decision-making in highly interactiv...
In policy learning for robotic manipulation, sample efficiency is of
par...
Self-supervised multi-object trackers have the potential to leverage the...
Perception datasets for agriculture are limited both in quantity and
div...
We present CARTO, a novel approach for reconstructing multiple articulat...
Visual odometry is a fundamental task for many applications on mobile de...
Operating a robot in the open world requires a high level of robustness ...
Uncertainty estimation is crucial in safety-critical settings such as
au...
Self-supervised feature learning enables perception systems to benefit f...
Lane graph estimation is an essential and highly challenging task in
aut...
Bird's-Eye-View (BEV) semantic maps have become an essential component o...
Interactive Imitation Learning (IIL) is a branch of Imitation Learning (...
A key component of graph-based SLAM systems is the ability to detect loo...
Accurate localization is a critical requirement for most robotic tasks. ...
Setting up robot environments to quickly test newly developed algorithms...
Machine learning has significantly enhanced the abilities of robots, ena...
Despite its importance in both industrial and service robotics, mobile
m...
Amodal panoptic segmentation aims to connect the perception of the world...
Recent advances in vision-based navigation and exploration have shown
im...
In recent years, policy learning methods using either reinforcement or
i...
Online 3D multi-object tracking (MOT) has witnessed significant research...
Object detection, for the most part, has been formulated in the euclidea...
While lifelong SLAM addresses the capability of a robot to adapt to chan...
Humans have the remarkable ability to perceive objects as a whole, even ...
The success of deep learning in recent years has lead to a rising demand...
As robotic systems become more and more capable of assisting humans in t...
Object recognition for the most part has been approached as a one-hot pr...
In this technical report, we describe our EfficientLPT architecture that...
Audio-visual navigation combines sight and hearing to navigate to a
soun...
A core challenge for an autonomous agent acting in the real world is to ...
Learning to solve complex manipulation tasks from visual observations is...
Scene understanding is a pivotal task for autonomous vehicles to safely
...
Panoptic scene understanding and tracking of dynamic agents are essentia...
Bird's-Eye-View (BEV) maps have emerged as one of the most powerful
repr...
Multi-view classification is inspired by the behavior of humans, especia...
Loop closure detection is an essential component of Simultaneous Localiz...
Attributes of sound inherent to objects can provide valuable cues to lea...
Panoptic segmentation of point clouds is a crucial task that enables
aut...
Mobile manipulation tasks remain one of the critical challenges for the
...
The exponentially increasing advances in robotics and machine learning a...
In this technical report, we present key details of our winning panoptic...
Dynamic objects have a significant impact on the robot's perception of t...