101 citations · 189 across the 27 of their papers we have counts for
28 papers
Real-Time Planning Under Uncertainty for AUVs Using Virtual Maps
Ivana Collado-Gonzalez, John McConnell, Jinkun Wang +2
Reliable localization is an essential capability for marine robots navigating in GPS-denied environments. SLAM, commonly used to mitigate dead reckoning errors, still fails in feat…
Mobile Manipulation Platform for Autonomous Indoor Inspections in Low-Clearance Areas
Erik Pearson, Paul Szenher, Christine Huang +1
Mobile manipulators have been used for inspection, maintenance and repair tasks over the years, but there are some key limitations. Stability concerns typically require mobile plat…
A Robust and Rapidly Deployable Waypoint Navigation Architecture for Long-Duration Operations in GPS-Denied Environments
Erik Pearson, Brendan Englot
For long-duration operations in GPS-denied environments, accurate and repeatable waypoint navigation is an essential capability. While simultaneous localization and mapping (SLAM)…
Robust Unmanned Surface Vehicle Navigation with Distributional Reinforcement Learning
Xi Lin, John McConnell, Brendan Englot
Autonomous navigation of Unmanned Surface Vehicles (USV) in marine environments with current flows is challenging, and few prior works have addressed the sensorbased navigation pro…
Robust Route Planning with Distributional Reinforcement Learning in a Stochastic Road Network Environment
Xi Lin, Paul Szenher, John D. Martin +1
Route planning is essential to mobile robot navigation problems. In recent years, deep reinforcement learning (DRL) has been applied to learning optimal planning policies in stocha…
Monocular Simultaneous Localization and Mapping using Ground Textures
Kyle M. Hart, Brendan Englot, Ryan P. O'Shea +2
Recent work has shown impressive localization performance using only images of ground textures taken with a downward facing monocular camera. This provides a reliable navigation me…
DRACo-SLAM: Distributed Robust Acoustic Communication-efficient SLAM for Imaging Sonar Equipped Underwater Robot Teams
John McConnell, Yewei Huang, Paul Szenher +2
An essential task for a multi-robot system is generating a common understanding of the environment and relative poses between robots. Cooperative tasks can be executed only when a…
A Fully-autonomous Framework of Unmanned Surface Vehicles in Maritime Environments using Gaussian Process Motion Planning
Jiawei Meng, Ankita Humne, Richard Bucknall +2
Unmanned surface vehicles (USVs) are of increasing importance to a growing number of sectors in the maritime industry, including offshore exploration, marine transportation and def…
Virtual Maps for Autonomous Exploration of Cluttered Underwater Environments
Jinkun Wang, Fanfei Chen, Yewei Huang +3
We consider the problem of autonomous mobile robot exploration in an unknown environment, taking into account a robot's coverage rate, map uncertainty, and state estimation uncerta…
Overhead Image Factors for Underwater Sonar-based SLAM
John McConnell, Fanfei Chen, Brendan Englot
Simultaneous localization and mapping (SLAM) is a critical capability for any autonomous underwater vehicle (AUV). However, robust, accurate state estimation is still a work in pro…
LVI-SAM: Tightly-coupled Lidar-Visual-Inertial Odometry via Smoothing and Mapping
Tixiao Shan, Brendan Englot, Carlo Ratti +1
We propose a framework for tightly-coupled lidar-visual-inertial odometry via smoothing and mapping, LVI-SAM, that achieves real-time state estimation and map-building with high ac…
Zero-Shot Reinforcement Learning on Graphs for Autonomous Exploration Under Uncertainty
Fanfei Chen, Paul Szenher, Yewei Huang +4
This paper studies the problem of autonomous exploration under localization uncertainty for a mobile robot with 3D range sensing. We present a framework for self-learning a high-pe…
Robust Place Recognition using an Imaging Lidar
Tixiao Shan, Brendan Englot, Fabio Duarte +2
We propose a methodology for robust, real-time place recognition using an imaging lidar, which yields image-quality high-resolution 3D point clouds. Utilizing the intensity reading…
Predictive 3D Sonar Mapping of Underwater Environments via Object-specific Bayesian Inference
John McConnell, Brendan Englot
Recent work has achieved dense 3D reconstruction with wide-aperture imaging sonar using a stereo pair of orthogonally oriented sonars. This allows each sonar to observe a spatial d…
Fast Design Space Exploration of Nonlinear Systems: Part I
Sanjai Narain, Emily Mak, Dana Chee +4
System design tools are often only available as input-output blackboxes: for a given design as input they compute an output representing system behavior. Blackboxes are intended to…
Robot Design With Neural Networks, MILP Solvers and Active Learning
Sanjai Narain, Emily Mak, Dana Chee +6
Central to the design of many robot systems and their controllers is solving a constrained blackbox optimization problem. This paper presents CNMA, a new method of solving this pro…
A Receding Horizon Multi-Objective Planner for Autonomous Surface Vehicles in Urban Waterways
Tixiao Shan, Wei Wang, Brendan Englot +2
We propose a novel receding horizon planner for an autonomous surface vehicle (ASV) performing path planning in urban waterways. Feasible paths are found by repeatedly generating a…
Variational Filtering with Copula Models for SLAM
John D. Martin, Kevin Doherty, Caralyn Cyr +2
The ability to infer map variables and estimate pose is crucial to the operation of autonomous mobile robots. In most cases the shared dependency between these variables is modeled…
Autonomous Exploration Under Uncertainty via Deep Reinforcement Learning on Graphs
Fanfei Chen, John D. Martin, Yewei Huang +2
We consider an autonomous exploration problem in which a range-sensing mobile robot is tasked with accurately mapping the landmarks in an a priori unknown environment efficiently i…
Fusing Concurrent Orthogonal Wide-aperture Sonar Images for Dense Underwater 3D Reconstruction
John McConnell, John D. Martin, Brendan Englot
We propose a novel approach to handling the ambiguity in elevation angle associated with the observations of a forward looking multi-beam imaging sonar, and the challenges it poses…
LIO-SAM: Tightly-coupled Lidar Inertial Odometry via Smoothing and Mapping
Tixiao Shan, Brendan Englot, Drew Meyers +3
We propose a framework for tightly-coupled lidar inertial odometry via smoothing and mapping, LIO-SAM, that achieves highly accurate, real-time mobile robot trajectory estimation a…
Simulation-based Lidar Super-resolution for Ground Vehicles
Tixiao Shan, Jinkun Wang, Fanfei Chen +2
We propose a methodology for lidar super-resolution with ground vehicles driving on roadways, which relies completely on a driving simulator to enhance, via deep learning, the appa…
A Lexicographic Search Method for Multi-Objective Motion Planning
Tixiao Shan, Brendan Englot
We propose a novel method for multi-objective motion planning problems by leveraging the paradigm of lexicographic optimization and applying it for the first time to graph search o…
Stochastically Dominant Distributional Reinforcement Learning
John D. Martin, Michal Lyskawinski, Xiaohu Li +1
We describe a new approach for managing aleatoric uncertainty in the Reinforcement Learning (RL) paradigm. Instead of selecting actions according to a single statistic, we propose…