Cooperative Perception: A Resource-Efficient Framework for Multi-Drone 3D Scene Reconstruction Using Federated Diffusion and NeRF
Fuente:
arXiv
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| _version_ | 1866909718372417536 |
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| author | Pourmandi, Massoud |
| author_facet | Pourmandi, Massoud |
| contents | The proposal introduces an innovative drone swarm perception system that aims to solve problems related to computational limitations and low-bandwidth communication, and real-time scene reconstruction. The framework enables efficient multi-agent 3D/4D scene synthesis through federated learning of shared diffusion model and YOLOv12 lightweight semantic extraction and local NeRF updates while maintaining privacy and scalability. The framework redesigns generative diffusion models for joint scene reconstruction, and improves cooperative scene understanding, while adding semantic-aware compression protocols. The approach can be validated through simulations and potential real-world deployment on drone testbeds, positioning it as a disruptive advancement in multi-agent AI for autonomous systems. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2508_00967 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Cooperative Perception: A Resource-Efficient Framework for Multi-Drone 3D Scene Reconstruction Using Federated Diffusion and NeRF Pourmandi, Massoud Artificial Intelligence Robotics 68T07, 68T45, 93C85 I.2.6; I.2.9; I.2.10; I.4.8 The proposal introduces an innovative drone swarm perception system that aims to solve problems related to computational limitations and low-bandwidth communication, and real-time scene reconstruction. The framework enables efficient multi-agent 3D/4D scene synthesis through federated learning of shared diffusion model and YOLOv12 lightweight semantic extraction and local NeRF updates while maintaining privacy and scalability. The framework redesigns generative diffusion models for joint scene reconstruction, and improves cooperative scene understanding, while adding semantic-aware compression protocols. The approach can be validated through simulations and potential real-world deployment on drone testbeds, positioning it as a disruptive advancement in multi-agent AI for autonomous systems. |
| title | Cooperative Perception: A Resource-Efficient Framework for Multi-Drone 3D Scene Reconstruction Using Federated Diffusion and NeRF |
| topic | Artificial Intelligence Robotics 68T07, 68T45, 93C85 I.2.6; I.2.9; I.2.10; I.4.8 |
| url | https://arxiv.org/abs/2508.00967 |