Reflection-Based Relative Localization for Cooperative UAV Teams Using Active Markers

TL;DR

This paper tackles the problem of onboard relative localization for cooperative UAV teams in environments where external infrastructure is unreliable or unavailable. It introduces a camera-only, reflection-based localization method that uses the diffuse and specular reflections of active markers on surfaces, without requiring prior knowledge of marker configurations or surface properties. By modeling the observations as intersections of elliptical cones and refining with a robust particle filter, the approach achieves reliable relative positioning at ranges exceeding $30\text{ m}$ and outperforms the state-of-the-art (UVDAR) in outdoor scenarios, while remaining effective indoors across floor types and lighting. The work significantly expands the practical potential of micro-UAV swarms in challenging real-world environments, including marine deployments, and provides a path toward infrastructure-free, scalable cooperative localization.

Abstract

Reflections of active markers in the environment are a common source of ambiguity in onboard visual relative localization. This work presents a novel approach for onboard relative localization in multi-robot teams that exploits these typically unwanted reflections of active markers in the environment. It operates without prior knowledge of robot size or predefined marker configurations and remains independent of surface properties, an essential feature for heterogeneous micro-aerial swarms cooperating in unknown environments. It explicitly accounts for uncertainties caused by non-flat surfaces, with a particular focus on dynamic water surfaces, which are especially relevant for marine deployments. We validated the approach in both indoor and outdoor experiments, demonstrating that the proposed reflection-based localization system operates reliably without prior knowledge of team member size and achieves greater effective range (above 30 m) and accuracy than state-of-the-art methods. The video and source code of this work will be made publicly available after publication.

Figures (10)

• Figure 1: Outdoor (left) and indoor dark (right) experiments: A UAV estimates the relative position by using surface reflections from active markers attached to a team member UAV. Blue boxes: the UAV with active markers attached. Red box: Surface reflections of the light emitted by the UAV.
• Figure 2: (a) UVDAR system estimating relative position using the known spacing between UV-LED attached to a UAV liceaOpticalCommunicationbasedIdentification2025. (b) UV-LED array attached to a UAV, used in our indoor experiment for relative localization.
• Figure 3: Excerpt from an outdoor experiment showing active markers attached to the UAV (blue) and their diffuse reflections on the water surface (red), captured onboard the UAV.
• Figure 4: Two extreme cases: Incident light (blue) undergoes (a) specular and (b) diffuse reflection (red).
• Figure 5: One UAV equipped with a camera (yellow) constructs an elliptical cone based on the diffuse reflections of light emitted by the transmitting UAV (top left). (a) Side view of our approach, showing the potential location of the transmitting UAV determined by the intersection of two elliptical cones (gray area). (b) Top-down view of the observer UAV with the ellipse around the diffuse reflection.