Spencer Hallyburton — accepted AI-conference papers

2025

RaGNNarok: A Light-Weight Graph Neural Network for Enhancing Radar Point Clouds on Unmanned Ground Vehicles

David Hunt, Shaocheng Luo, Spencer Hallyburton, Shafii Nillongo, Yi Li, Tingjun Chen +1

IROS 2025

Current lidar and camera-based solutions for low-cost indoor mobile robots have limitations such as poor performance in visually obscured environments, high computational overhead for data processing, and high costs for lidars. In contrast, mmWave radar sensors offer a cost-effective and lightweight

Cited by 0 Source ↗Scholar ↗

2024

RadCloud: Real-Time High-Resolution Point Cloud Generation Using Low-Cost Radars for Aerial and Ground Vehicles

David Hunt, Shaocheng Luo, Amir Khazraei, Xiao Zhang, Spencer Hallyburton, Tingjun Chen +1

ICRA 2024poster

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-constrained platforms commonly used in unmanned aerial and ground vehicles (UAVs and UGVs, respectively); such point clouds…

Cited by 5 Source ↗Scholar ↗