室内3D无人机跟踪多模式数据集
Jakub Rosner1, Tomasz Krzeszowski2,3, Adam Świtoński1,4
1Polish-Japanese Academy of Information Technology, ul. Koszykowa 86, 02-008, Warsaw, Poland.
Scientific data
|February 12, 2025
概括
本研究介绍了DPJAIT用于无人机3D跟踪的多式联络数据集,包括模拟和现实数据. 它可以实现先进的无人机本地化和相机校准应用程序.
科学领域:
- 机器人和计算机视觉 机器人和计算机视觉
- 传感器融合和数据采集
背景情况:
- 准确的3D无人机定位对于自主导航和空中机器人非常重要.
- 现有的数据集往往缺乏强大的3D跟踪算法开发所需的多式联络丰富性.
研究的目的:
- 为了引入无人机姿势和精确的Jittering跟踪 (DPJAIT) 多式联机数据集的Jittering.
- 为开发和评估3D无人机跟踪算法提供全面的资源.
- 为了证明数据集在无人机姿势估计中的新应用.
主要方法:
- 使用模拟和现实世界测量 (Vicon系统) 创建数据集.
- 集成同步的多摄像头视频序列和参考3D无人机位置.
- 包括已知3D位置的ArUco标记器和无人机上的RGB摄像头数据.
主要成果:
- DPJAIT数据集提供了两种变体:基于模拟的和真实测量的数据.
- 展示三种3D跟踪应用:摄像头投影,粒子群优化和基于ArUco标记器的外部矩阵确定.
- 使用黄金标准的移动捕捉技术验证无人机跟踪的准确性.
结论:
- DPJAIT数据集是推动无人机3D跟踪和定位研究的宝贵资源.
- 展示的应用突出显示了数据集对算法开发和性能评估的有用性.
- 这项工作有助于创建更强大,更准确的自主无人机系统.
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