5 papers
LLaViDA: A Large Language Vision Driving Assistant for Explicit Reasoning and Enhanced Trajectory Planning
Yudong Liu, Spencer Hallyburton, Jiwoo Kim +8
Trajectory planning is a fundamental yet challenging component of autonomous driving. End-to-end planners frequently falter under adverse weather, unpredictable human behavior, or…
RaGNNarok: A Light-Weight Graph Neural Network for Enhancing Radar Point Clouds on Unmanned Ground Vehicles
David Hunt, Shaocheng Luo, Spencer Hallyburton +4
Low-cost indoor mobile robots have gained popularity with the increasing adoption of automation in homes and commercial spaces. However, existing lidar and camera-based solutions h…
RadCloud: Real-Time High-Resolution Point Cloud Generation Using Low-Cost Radars for Aerial and Ground Vehicles
David Hunt, Shaocheng Luo, Amir Khazraei +4
In this work, we present RadCloud, a novel real time framework for directly obtaining higher-resolution lidar-like 2D point clouds from low-resolution radar frames on resource-cons…
Datasets, Models, and Algorithms for Multi-Sensor, Multi-agent Autonomy Using AVstack
R. Spencer Hallyburton, Miroslav Pajic
Recent advancements in assured autonomy have brought autonomous vehicles (AVs) closer to fruition. Despite strong evidence that multi-sensor, multi-agent (MSMA) systems can yield s…
Learning-Based Vulnerability Analysis of Cyber-Physical Systems
Amir Khazraei, Spencer Hallyburton, Qitong Gao +2
This work focuses on the use of deep learning for vulnerability analysis of cyber-physical systems (CPS). Specifically, we consider a control architecture widely used in CPS (e.g.,…