Welcome to the University of Arizona Radar Lab! We focus on radar signal processing, multimodal sensor fusion, machine learning with an emphasis on sensors, and radar imaging.
Our newly developed website provides details about our research projects, members, publications, resources, and latest news. Please visit the site for the most up-to-date information:
A unified benchmarking framework for cooperative autonomous driving with Multi-Agent Reinforcement Learning (MARL) capabilities, extending OpenCDA's full-stack simulation platform with distributed training infrastructure for intelligent multi-agent driving policies under CARLA+SUMO co-simulation.
CalibRefine: Deep Learning-Based Online Automatic Targetless LiDAR–Camera Calibration with Iterative and Attention-Driven Post-Refinement
Code for our paper: Radar-Camera Fused Multi-Object Tracking: Online Calibration and Common Feature
ROS 1 Package to collect, visualize, and process data from Hesai Lidar, TI mmWave Radar, and USB Camera for sensor fusion
Code for our paper: TransRAD: Retentive Vision Transformer for Enhanced Radar Object Detection
Code for our paper: Online Targetless Radar-Camera Extrinsic Calibration Based on the Common Features of Radar and Camera
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