Articles with public access mandates - Ryan M. EusticeLearn more
Available somewhere: 17
WaterGAN: Unsupervised generative network to enable real-time color correction of monocular underwater images
J Li, KA Skinner, RM Eustice, M Johnson-Roberson
IEEE Robotics and Automation letters 3 (1), 387-394, 2018
Mandates: US National Science Foundation, US Department of Defense, US National …
Contact-aided invariant extended Kalman filtering for robot state estimation
R Hartley, M Ghaffari, RM Eustice, JW Grizzle
The International Journal of Robotics Research 39 (4), 402-430, 2020
Mandates: US National Science Foundation
Robust LIDAR localization using multiresolution Gaussian mixture maps for autonomous driving
RW Wolcott, RM Eustice
The International Journal of Robotics Research 36 (3), 292-319, 2017
Mandates: US Department of Defense
Multipolicy decision-making for autonomous driving via changepoint-based behavior prediction: Theory and experiment
E Galceran, AG Cunningham, RM Eustice, E Olson
Autonomous Robots 41, 1367-1382, 2017
Mandates: US Department of Defense
Pairwise consistent measurement set maximization for robust multi-robot map merging
JG Mangelson, D Dominic, RM Eustice, R Vasudevan
2018 IEEE International Conference on Robotics and Automation (ICRA), 2916-2923, 2018
Mandates: US Department of Defense
Pose-graph SLAM using Forward-looking Sonar
J Li, M Kaess, RM Eustice, M Johnson-Roberson
IEEE Robotics and Automation Letters 3 (3), 2330-2337, 2018
Mandates: US Department of Energy, US Department of Defense
Bayesian Spatial Kernel Smoothing for Scalable Dense Semantic Mapping
L Gan, R Zhang, JW Grizzle, RM Eustice, M Ghaffari
IEEE Robotics and Automation Letters 5 (2), 790-797, 2020
Mandates: US National Science Foundation
Legged robot state-estimation through combined forward kinematic and preintegrated contact factors
R Hartley, J Mangelson, L Gan, MG Jadidi, JM Walls, RM Eustice, ...
2018 IEEE International Conference on Robotics and Automation (ICRA), 4422-4429, 2018
Mandates: US National Science Foundation, US Department of Defense
Characterizing the Uncertainty of Jointly Distributed Poses in the Lie Algebra
JG Mangelson, M Ghaffari, R Vasudevan, RM Eustice
IEEE Transactions on Robotics 36 (5), 1371-1388, 2020
Mandates: US Department of Defense
Hybrid Contact Preintegration for Visual-Inertial-Contact State Estimation Using Factor Graphs
R Hartley, MG Jadidi, L Gan, JK Huang, JW Grizzle, RM Eustice
2018 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2018
Mandates: US National Science Foundation
Semantic Iterative Closest Point through Expectation-Maximization
SA Parkison, L Gan, MG Jadidi, RM Eustice
British Machine Vision Conference (BMVC), 1-17, 2018
Mandates: US National Science Foundation
Mapping underwater ship hulls using a model-assisted bundle adjustment framework
P Ozog, M Johnson-Roberson, RM Eustice
Robotics and Autonomous Systems 87, 329-347, 2017
Mandates: US Department of Defense
Energy-Based Legged Robots Terrain Traversability Modeling via Deep Inverse Reinforcement Learning
L Gan, JW Grizzle, RM Eustice, M Ghaffari
IEEE Robotics and Automation Letters 7 (4), 8807-8814, 2022
Mandates: US National Science Foundation
Guaranteed globally optimal planar pose graph and landmark SLAM via sparse-bounded sums-of-squares programming
JG Mangelson, J Liu, RM Eustice, R Vasudevan
2019 International Conference on Robotics and Automation (ICRA), 9306-9312, 2019
Mandates: US Department of Defense
Multitask Learning for Scalable and Dense Multilayer Bayesian Map Inference
L Gan, Y Kim, JW Grizzle, JM Walls, A Kim, RM Eustice, M Ghaffari
IEEE Transactions on Robotics, 2022
Mandates: US National Science Foundation
Communication Constrained Trajectory Alignment For Multi-Agent Inspection via Linear Programming
JG Mangelson, R Vasudevan, RM Eustice
OCEANS 2018 MTS/IEEE Charleston, 1-8, 2018
Mandates: US Department of Defense
A Robust Keyframe-based Visual SLAM for RGB-D Cameras in Challenging Scenarios
X Lin, Y Huang, D Sun, TY Lin, B Englot, RM Eustice, M Ghaffari
IEEE Access, 2023
Mandates: US National Science Foundation, US Department of Defense
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