# Omni-swarm: A Decentralized Omnidirectional Visual-Inertial-UWB State Estimation System for Aerial Swarms

arXiv: https://arxiv.org/abs/2103.04131 · HTML: https://mlsanity.com/paper/2103.04131/

## Key facts

- Cited by 12 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 6 Mar 2021.

## Built on by (most cited first, 12 of 12)

- [General Place Recognition Survey: Towards Real-World Autonomy](https://mlsanity.com/paper/2405.04812/) (2024)
- [Ultra Inertial Poser: Scalable Motion Capture and Tracking from Sparse Inertial Sensors and Ultra-Wideband Ranging](https://mlsanity.com/paper/2404.19541/) (2024)
- [LF-VISLAM: A SLAM Framework for Large Field-of-View Cameras with Negative Imaging Plane on Mobile Agents](https://mlsanity.com/paper/2209.05167/) (2022)
- [Group Inertial Poser: Multi-Person Pose and Global Translation from Sparse Inertial Sensors and Ultra-Wideband Ranging](https://mlsanity.com/paper/2510.21654/) (2025)
- [ULOC: Learning to Localize in Complex Large-Scale Environments with Ultra-Wideband Ranges](https://mlsanity.com/paper/2409.11122/) (2024)
- [MSI-NeRF: Linking Omni-Depth with View Synthesis through Multi-Sphere Image aided Generalizable Neural Radiance Field](https://mlsanity.com/paper/2403.10840/) (2024)
- [EdgePoint2: Compact Descriptors for Superior Efficiency and Accuracy](https://mlsanity.com/paper/2504.17280/) (2025)
- [Relative Localization of Mobile Robots with Multiple Ultra-WideBand Ranging Measurements](https://mlsanity.com/paper/2107.08842/) (2021)
- [Semi-distributed Cross-modal Air-Ground Relative Localization](https://mlsanity.com/paper/2511.06749/) (2025)
- [CSMapping: Scalable Crowdsourced Semantic Mapping and Topology Inference for Autonomous Driving](https://mlsanity.com/paper/2512.03510/) (2025)
- [Gaussian Variational Inference with Non-Gaussian Factors for State Estimation: A UWB Localization Case Study](https://mlsanity.com/paper/2512.19855/) (2025)
- [Federated 3D Gaussian Splatting for Large-Scale Scene Reconstruction at Wireless Edge](https://mlsanity.com/paper/2609.32177/) (2026)

## Abstract (arXiv)

Decentralized state estimation is one of the most fundamental components of autonomous aerial swarm systems in GPS-denied areas yet it still remains a highly challenging research topic. Omni-swarm, a decentralized omnidirectional visual-inertial-UWB state estimation system for aerial swarms, is proposed in this paper to address this research niche. To solve the issues of observability, complicated initialization, insufficient accuracy, and lack of global consistency, we introduce an omnidirectional perception front-end in Omni-swarm. It consists of stereo wide-FoV cameras and ultra-wideband sensors, visual-inertial odometry, multi-drone map-based localization, and visual drone tracking algorithms. The measurements from the front-end are fused with graph-based optimization in the back-end. The proposed method achieves centimeter-level relative state estimation accuracy while guaranteeing global consistency in the aerial swarm, as evidenced by the experimental results. Moreover, supported by Omni-swarm, inter-drone collision avoidance can be accomplished without any external devices, demonstrating the potential of Omni-swarm as the foundation of autonomous aerial swarms.