无人机载有地图算法用于低空和高速无人机应用
Jincheng Zhang1, Artur Wolek2, Andrew R Willis1
1Department of Electrical and Computer Engineering, University of North Carolina at Charlotte, Charlotte, NC 28223, USA.
Sensors (Basel, Switzerland)
|April 13, 2024
概括
本研究评估了无人机 (UAV) 地图算法在现实的模拟中. 在无人机导航中,DSOL,SDSO和DSO在速度和准确性之间提供了不同的权衡.
科学领域:
- 机器人和计算机视觉 机器人和计算机视觉
- 自主系统的传感器融合和感知.
背景情况:
- 无人驾驶飞行器 (UAV) 技术的进步需要强大的地图解决方案,用于低高度,高速操作.
- 准确的实时环境绘图对于无人机导航和任务成功至关重要.
研究的目的:
- 分析用于无人机应用的最先进的传感器和映射算法.
- 在高保真模拟环境中评估直射散射计量 (DSO),立体 DSO (SDSO) 和 DSO Lite (DSOL) 的性能.
主要方法:
- 开发一种新的实验结构,通过Cesium Tiles插件将AirSim模拟器与谷歌3D地图集成在一起.
- 基于几何精度和计算速度的DSO,SDSO和DSOL的比较性能评估.
- 实验在一个高度现实的模拟环境中进行,模仿真实世界的条件.
主要成果:
- 量化每个算法的计算性能和地图准确性之间的权衡.
- 确定DSOL是有限的计算资源的无人机的最佳选择.
- 推用于有效载荷能力和中等计算能力的系统的SDSO.
结论:
- 无人机映射的算法选择需要平衡计算需求与所需的地图密度和准确性.
- DSO适用于要求密集映射的单摄像机应用.
- 该研究为研究人员提供了关键的见解,以选择最适合特定无人机应用程序的绘图算法.
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