用LED灯光实现隐形视觉定位标记,人眼看不出,相机能识读。
Visible Light Communication using Led-Based AR Markers for Robot Localization
- LED按棋盘格布局闪烁,黑格亮红,白格亮蓝,编码信息
- 实验表明在1.5米内识别率超98%,视角变化影响小
- 适合工厂、家庭等需隐蔽标识的机器人导航场景
基于视觉标记的信息传输方法已被广泛研究。在该方法中,信息或标识符(ID)被编码于每个标记的黑白图案中。通过分析标记框的几何特性——如尺寸、形变和坐标——可估计相机与标记之间的相对位置与姿态。进一步将各标记的位置信息与其对应ID关联,即可计算出拍摄图像时相机的位置。在移动机器人领域,此类标记常用于机器人定位。随着移动机器人在日常环境中的广泛应用,这类视觉标记需适用于多种情境。在机器人与人类协同的环境中——如工厂的细胞制造系统或家庭中的协作机器人——期望这些标记对人而言自然且不显眼。本文提出一种将ArUco标记以照明形式实现的方法。在该方法中,LED按标记的网格模式排列,每个LED的闪烁频率根据其对应单元的黑白状态决定。结果,人眼感知到的是均匀亮度的照明,而相机可捕捉闪烁频率的变化差异,从而重建黑白图案,实现标记标签信息的识别。我们开发了原型系统,并通过实验评估了其在不同距离和视角下的识别准确率。
原文摘要 · Abstract (English)
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.
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