Visible Light Communication using Led-Based AR Markers for Robot Localization

TL;DR

This paper introduces a novel LED-based AR marker system for robot localization that uses visible light communication to encode marker information, enabling natural-looking markers that are unobtrusive to humans while maintaining high recognition accuracy.

Contribution

The paper presents a new LED illumination method for AR markers that allows camera-based recognition through blinking frequency analysis, improving marker naturalness and usability in human-robot environments.

Findings

High recognition accuracy across different distances

Robust performance under various viewing angles

Effective encoding of marker information via LED blinking

Abstract

A method of information transmission using visual markers has been widely studied. In this approach, information or identifiers (IDs) are encoded in the black-and-white pattern of each marker. By analyzing the geometric properties of the marker frame - such as its size, distortion, and coordinates - the relative position and orientation between the camera and the marker can be estimated. Furthermore, by associating the positional information of each marker with its corresponding ID, the position of the camera that takes the image picture can be calculated. In the field of mobile robotics, such markers are commonly utilized for robot localization. As mobile robots become more widely used in everyday environments, such visual markers are expected to be utilized across various contexts. In environments where robots collaborate with humans - such as in cell-based manufacturing systems in factories or in domestic settings with partner robots - it is desirable for such markers to be designed in a manner that appears natural and unobtrusive to humans. In this paper, we propose a method for implementing an ArUco marker in the form of illumination. In the proposed method, LEDs are arranged in accordance with the grid pattern of the marker, and the blinking frequency of each LED is determined based on the corresponding black or white cell. As a result, the illumination appears uniformly bright to the human eye, while the camera can capture variations in the blinking frequency. From these differences, the black-and-white pattern can be reconstructed, enabling the identification of the marker's tag information. We develop a prototype system, and conduct experiments which are conducted to evaluate its performance in terms of recognition accuracy under varying distances and viewing angles with respect to the ArUco marker.