5 papers
A Knowledge-Graph Translation Layer for Mission-Aware Multi-Agent Path Planning in Spatiotemporal Dynamics
Edward Holmberg, Elias Ioup, Mahdi Abdelguerfi
The coordination of autonomous agents in dynamic environments is hampered by the semantic gap between high-level mission objectives and low-level planner inputs. To address this, w…
Accelerating HEC-RAS: A Recurrent Neural Operator for Rapid River Forecasting
Edward Holmberg, Pujan Pokhrel, Maximilian Zoch +9
Physics-based solvers like HEC-RAS provide high-fidelity river forecasts but are too computationally intensive for on-the-fly decision-making during flood events. The central chall…
Physics-Informed Neural Network Surrogate Models for River Stage Prediction
Maximilian Zoch, Edward Holmberg, Pujan Pokhrel +8
This work investigates the feasibility of using Physics-Informed Neural Networks (PINNs) as surrogate models for river stage prediction, aiming to reduce computational cost while m…
Knowledge Graph-Based Multi-Agent Path Planning in Dynamic Environments using WAITR
Ted Edward Holmberg, Elias Ioup, Mahdi Abdelguerfi
This paper addresses the challenge of multi-agent path planning for efficient data collection in dynamic, uncertain environments, exemplified by autonomous underwater vehicles (AUV…
Data Visualization to Evaluate and Facilitate Targeted Data Acquisitions in Support of a Real-time Ocean Forecasting System
Edward Holmberg
A robust evaluation toolset has been designed for Naval Research Laboratory's Real-Time Ocean Forecasting System RELO with the purpose of facilitating an adaptive sampling strategy…