# Towards agile multi-robot systems in the real world: Fast onboard tracking of active blinking markers for relative localization

arXiv: https://arxiv.org/abs/2502.01172 · HTML: https://mlsanity.com/paper/2502.01172/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 8 of its 41 references that are in the map.
- First posted on arXiv 3 Feb 2025.

## Builds on (most cited first, 8 of 8)

- [Real-time 6-DoF Pose Estimation by an Event-based Camera using Active LED Markers](https://mlsanity.com/paper/2310.16618/) (2023)
- [Decentralized Visual-Inertial-UWB Fusion for Relative State Estimation of Aerial Swarm](https://mlsanity.com/paper/2003.05138/) (2020)
- [MRS Drone: A Modular Platform for Real-World Deployment of Aerial Multi-Robot Systems](https://mlsanity.com/paper/2306.07229/) (2023)
- [Cooperative Multi-Agent Trajectory Generation with Modular Bayesian Optimization](https://mlsanity.com/paper/2206.00726/) (2022)
- [UWB-based system for UAV Localization in GNSS-Denied Environments: Characterization and Dataset](https://mlsanity.com/paper/2003.04380/) (2020)
- [Bio-Inspired Compact Swarms of Unmanned Aerial Vehicles without Communication and External Localization](https://mlsanity.com/paper/2303.02989/) (2023)
- [Optical communication-based identification for multi-UAV systems: theory and practice](https://mlsanity.com/paper/2302.04770/) (2023)
- [Marker-Based Localisation System Using an Active PTZ Camera and CNN-Based Ellipse Detection](https://mlsanity.com/paper/2311.02937/) (2023)

## Abstract (arXiv)

A novel onboard tracking approach enabling vision-based relative localization and communication using Active blinking Marker Tracking (AMT) is introduced in this article. Active blinking markers on multi-robot team members improve the robustness of relative localization for aerial vehicles in tightly coupled multi-robot systems during real-world deployments, while also serving as a resilient communication system. Traditional tracking algorithms struggle with fast-moving blinking markers due to their intermittent appearance in camera frames and the complexity of associating multiple of these markers across consecutive frames. AMT addresses this by using weighted polynomial regression to predict the future appearance of active blinking markers while accounting for uncertainty in the prediction. In outdoor experiments, the AMT approach outperformed state-of-the-art methods in tracking density, accuracy, and complexity. The experimental validation of this novel tracking approach for relative localization and optical communication involved testing motion patterns motivated by our research on agile multi-robot deployment.