1 citations · 2 across the 12 of their papers we have counts for
7 papers · 1 filter
LDLT -Lipschitz Network: Generalized Deep End-To-End Lipschitz Network Construction
Marius F. R. Juston, Ramavarapu S. Sreenivas, Dustin Nottage +1
Deep residual networks (ResNets) have demonstrated outstanding success in computer vision tasks, attributed to their ability to maintain gradient flow through deep architectures. S…
Safety Monitor for Off-Road Planning with Uncertainty Bounded Bekker Costs
Akshay Naik, Ramavarapu S. Sreenivas, William R. Norris +3
Reliable off-road autonomy requires operational constraints so that behavior stays predictable and safe when soil strength is uncertain. This paper presents a runtime assurance saf…
Hybrid Terrain-Aware Path Planning: Integrating VD-RRT* Exploration and VD-D* Lite Repair
Akshay Naik, William R. Norris, Dustin Nottage +1
Autonomous ground vehicles operating off-road must plan curvature-feasible paths while accounting for spatially varying soil strength and slope hazards in real time. We present a c…
In-Situ Soil-Property Estimation and Bayesian Mapping with a Simulated Compact Track Loader
W. Jacob Wagner, Ahmet Soylemezoglu, Katherine Driggs-Campbell
Existing earthmoving autonomy is largely confined to highly controlled and well-characterized environments due to the complexity of vehicle-terrain interaction dynamics and the par…
APECS: Adaptive Personalized Control System Architecture
Marius F. R. Juston, Alex Gisi, William R. Norris +2
This paper presents the Adaptive Personalized Control System (APECS) architecture, a novel framework for human-in-the-loop control. An architecture is developed which defines appro…
1-Lipschitz Network Initialization for Certifiably Robust Classification Applications: A Decay Problem
Marius F. R. Juston, Ramavarapu S. Sreenivas, William R. Norris +2
This paper discusses the weight parametrization of two standard 1-Lipschitz network architectures, the Almost-Orthogonal-Layers (AOL) and the SDP-based Lipschitz Layers (SLL). It e…
L-Lipschitz Gershgorin ResNet Network
Marius F. R. Juston, William R. Norris, Dustin Nottage +1
Deep residual networks (ResNets) have demonstrated outstanding success in computer vision tasks, attributed to their ability to maintain gradient flow through deep architectures. S…