5 citations · 13 across the 12 of their papers we have counts for
14 papers
Hybrid Adaptive Kalman Filtering for Data-Efficient Joint Tracking and Classification
Jiho Lee, Nisar R. Ahmed, Rebecca Russell
Kalman filtering performance is highly sensitive to model mismatch and noise covariance tuning. Learning-based approaches address these limitations but typically rely on supervised…
Deep Modeling of Non-Gaussian Aleatoric Uncertainty
Aastha Acharya, Caleb Lee, Marissa D'Alonzo +3
Deep learning offers promising new ways to accurately model aleatoric uncertainty in robotic state estimation systems, particularly when the uncertainty distributions do not confor…
Wide-Area Geolocalization with a Limited Field of View Camera in Challenging Urban Environments
Lena M. Downes, Ted J. Steiner, Rebecca L. Russell +1
Cross-view geolocalization, a supplement or replacement for GPS, localizes an agent within a search area by matching ground-view images to overhead images. Significant progress has…
Surrogate Neural Networks for Efficient Simulation-based Trajectory Planning Optimization
Evelyn Ruff, Rebecca Russell, Matthew Stoeckle +2
This paper presents a novel methodology that uses surrogate models in the form of neural networks to reduce the computation time of simulation-based optimization of a reference tra…
Learning to Forecast Aleatoric and Epistemic Uncertainties over Long Horizon Trajectories
Aastha Acharya, Rebecca Russell, Nisar R. Ahmed
Giving autonomous agents the ability to forecast their own outcomes and uncertainty will allow them to communicate their competencies and be used more safely. We accomplish this by…
Symmetry Detection in Trajectory Data for More Meaningful Reinforcement Learning Representations
Marissa D'Alonzo, Rebecca Russell
Knowledge of the symmetries of reinforcement learning (RL) systems can be used to create compressed and semantically meaningful representations of a low-level state space. We prese…