Virtual Radar: Real-Time Millimeter-Wave Radar Sensor Simulation for Perception-Driven Robotics
| Autor: | Hubert Zangl, Christian Schoffmann, Stephan Mühlbacher-Karrer, Barnaba Ubezio, Christoph Bohm |
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| Rok vydání: | 2021 |
| Předmět: |
Control and Optimization
Computer science Real-time computing Biomedical Engineering Graphics processing unit 02 engineering and technology law.invention Data modeling Computer graphics Acceleration Radar engineering details 0203 mechanical engineering Artificial Intelligence law 0202 electrical engineering electronic engineering information engineering Radar 020301 aerospace & aeronautics business.industry Mechanical Engineering 020206 networking & telecommunications Robotics Computer Science Applications Human-Computer Interaction Control and Systems Engineering Extremely high frequency Computer Vision and Pattern Recognition Artificial intelligence business |
| Zdroj: | IEEE Robotics and Automation Letters. 6:4704-4711 |
| ISSN: | 2377-3774 |
| DOI: | 10.1109/lra.2021.3068916 |
| Popis: | This article presents ViRa 1 1 Available online: https://vira.aau.at/ . , a real-time open-source millimeter-wave radar simulation framework for perception-driven robotic applications. ViRa provides $(i)$ raw data of radar sensors in real-time, simulation of $(ii)$ multi-antenna configurations for spatial estimation of objects, $(iii)$ wave penetration of non-conductive objects to infer information in occluded situations, $(iv)$ different radar beam patterns, and, $(v)$ configurations of radar sensors as given by real-world radars. By using ViRa, researchers can simulate radar sensors in different robotic scenarios and investigate radars prior to the installation. This allows an acceleration in the development of radar sensors for robotic applications without the need of real hardware. Contrary to simple model abstractions, which only output loose features, ViRa generates raw radar data using computer graphics techniques on graphics processing unit (GPU) level embedded inside a game engine environment. ViRa allows to feed data directly into machine learning frameworks, which enables further improvement in novel research directions, such as safe human-robot interaction or agile drone flights in obstacle-rich environments. The proposed simulation framework is validated with data from different scenarios in robotics such as human tracking for human-robot interaction. The obtained results are compared with a reference simulation framework and show significantly higher correlation when compared to real-world measurement data. |
| Databáze: | OpenAIRE |
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