Leading autonomous vehicle (AV) platforms and testing infrastructures are, unfortunately, proprietary and closed-source. Thus, it is difficult to evaluate how well safety-critical AVs perform and how safe they truly are. Similarly, few platforms exist for much-needed multi-agent analysis. To provide a starting point for analysis of sensor fusion and collaborative & distributed sensing, we design an accessible, modular sensing platform with AVstack. We build collaborative and distributed camera-radar fusion algorithms and demonstrate an evaluation ecosystem of AV datasets, physics-based simulators, and hardware in the physical world. This three-part ecosystem enables testing next-generation configurations that are prohibitively challenging in existing development platforms.
@article{arxiv.2303.07430,
title = {A Modular Platform For Collaborative, Distributed Sensor Fusion},
author = {R. Spencer Hallyburton and Nate Zelter and David Hunt and Kristen Angell and Miroslav Pajic},
journal= {arXiv preprint arXiv:2303.07430},
year = {2023}
}