The article develops an impact-resilient aerial robot (s-ARQ) equipped w...
Modeling dynamics is often the first step to making a vehicle autonomous...
To achieve autonomy in unknown and unstructured environments, we propose...
Although autonomy has gained widespread usage in structured and controll...
We present a method for solving the coverage problem with the objective ...
In active source seeking, a robot takes repeated measurements in order t...
Experimental design in field robotics is an adaptive human-in-the-loop
d...
Robotic exploration of unknown environments is fundamentally a problem o...
This paper reports on the state of the art in underground SLAM by discus...
Navigating off-road with a fast autonomous vehicle depends on a robust
p...
Legged robots can traverse a wide variety of terrains, some of which may...
Communication is an important capability for multi-robot exploration bec...
Search and rescue with a team of heterogeneous mobile robots in unknown ...
Multi-robot SLAM systems in GPS-denied environments require loop closure...
Lidar odometry has attracted considerable attention as a robust localiza...
Multi-robot exploration of complex, unknown environments benefits from t...
Real-world deployment of new technology and capabilities can be daunting...
We present a method for autonomous exploration of large-scale unknown
en...
This paper presents a light-weight frontend LiDAR odometry solution with...
One of the main challenges in autonomous robotic exploration and navigat...
A new belief space planning algorithm, called covariance steering Belief...
This work proposes a resilient and adaptive state estimation framework f...
Collision-free path planning is an essential requirement for autonomous
...
Although ground robotic autonomy has gained widespread usage in structur...
In order for a robot to explore an unknown environment autonomously, it ...
Enabling fully autonomous robots capable of navigating and exploring
lar...
State estimation for robots navigating in GPS-denied and
perceptually-de...
Unmanned aerial vehicles are rapidly evolving within the field of roboti...
We propose a framework for resilient autonomous navigation in perceptual...
Monocular depth inference has gained tremendous attention from researche...
This paper serves as one of the first efforts to enable large-scale and
...
Hybrid ground and aerial vehicles can possess distinct advantages over
g...
Robots and particularly drones are especially useful in exploring extrem...
In addition to conventional ground rovers, the Mars 2020 mission will se...
This article proposes a Novel Nonlinear Model Predictive Control (NMPC) ...
This article proposes a novel Nonlinear Model Predictive Control (NMPC)
...
Representing the environment is a fundamental task in enabling robots to...
This article proposes a novel unsupervised learning framework for detect...
In this report for the Nasa NIAC Phase I study, we present a mission
arc...
Simultaneous Localization and Mapping (SLAM) in large-scale, unknown, an...
Learning-based control aims to construct models of a system to use for
p...
In this paper we present a mission architecture and a robotic platform, ...
Highly accurate real-time localization is of fundamental importance for ...
Deep learning has enjoyed much recent success, and applying state-of-the...
Autonomous exploration of unknown environments with aerial vehicles rema...
Decision-making under uncertainty is a crucial ability for autonomous
sy...
The focus of this paper is on solving multi-robot planning problems in
c...