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Scaling Datasets for Multi-Sensor, Multi-Agent, and Multi-Domain Learning in Autonomous Systems

arXiv 2606.04444 ↗First posted 3 Jun 2026eess.IV cs.LGcited by 0

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Abstract (arXiv)

Existing datasets cannot support large-scale learning in multi-agent, multi-sensor, or multi-domain autonomy, where diversity and coordination are essential. We present a modular dataset generation pipeline that creates terabyte-scale, ground-truth-labeled data for ground, aerial, and infrastructure-based systems using the AVstack framework and CARLA simulator. Supporting single- and multi-agent configurations with flexible sensor suites, the pipeline enables controllable experimentation across challenging conditions. Representative perception and fusion studies show how generated data can support application-specific training and collaborative autonomy.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 25 of its 37 references that are in the map. First posted on arXiv 3 Jun 2026.

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25 of 37 references.

References · 25

  1. 2014Microsoft COCO: Common Objects in Contextcited by 17,498
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  4. 2019Scalability in Perception for Autonomous Driving: Waymo Open Datasetcited by 2,436
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  10. 2019Learning by Cheatingcited by 361
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  12. 2019End-to-End Model-Free Reinforcement Learning for Urban Driving using Implicit Affordancescited by 147
13 more
  1. 2021EagerMOT: 3D Multi-Object Tracking via Sensor Fusioncited by 83
  2. 2020AB3DMOT: A Baseline for 3D Multi-Object Tracking and New Evaluation Metricscited by 63
  3. 2022AVstack: An Open-Source, Reconfigurable Platform for Autonomous Vehicle Developmentcited by 6
  4. 2025LLaViDA: A Large Language Vision Driving Assistant for Explicit Reasoning and Enhanced Trajectory Planningcited by 5
  5. 2022A Cooperative Perception Environment for Traffic Operations and Controlcited by 3
  6. 2023Datasets, Models, and Algorithms for Multi-Sensor, Multi-agent Autonomy Using AVstackcited by 3
  7. 2025Security-Aware Sensor Fusion with MATE: the Multi-Agent Trust Estimatorcited by 3
  8. 2021V2X Misbehavior and Collective Perception Service: Considerations for Standardizationcited by 2
  9. 2022Exploiting Trust for Resilient Hypothesis Testing with Malicious Robotscited by 2
  10. 2024Bayesian Methods for Trust in Collaborative Multi-Agent Autonomycited by 2
  11. 2023A Modular Platform For Collaborative, Distributed Sensor Fusioncited by 1
  12. 2024A Multi-Agent Security Testbed for the Analysis of Attacks and Defenses in Collaborative Sensor Fusioncited by 1
  13. 2025Probabilistic Segmentation for Robust Field of View Estimationcited by 1

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