OpenNavSense平台:一个低成本的,开源的惯性导航系统,用于评估估计算法
Pablo Raul Yanyachi1, Jorch Mendoza-Chok1, Brayan Espinoza-Garcia1
1Instituto de Investigacion Astronomico y Aeroespacial Pedro Paulet, Universidad Nacional de San Agustin de Arequipa, 04000, Arequipa, Peru.
HardwareX
|January 27, 2025
概括
一个新的开源平台,INS OpenNavSense,为惯性导航系统 (INS) 提供了低成本的解决方案. 它使用FreeRTOS构建,有效地使用微电子机械系统 (MEMS) 传感器用于无人机导航和算法测试.
科学领域:
- 机器人和控制系统 机器人和控制系统
- 嵌入式系统工程 嵌入式系统工程
- 导航技术 导航技术 导航技术
背景情况:
- 惯性导航系统 (INS) 对于导航至关重要,但通常是昂贵和复杂的.
- 现有的INS解决方案依赖于高端传感器,限制了研究和开发的可访问性.
- 需要为INS研究提供具有成本效益和开源的平台.
研究的目的:
- 推出INS OpenNavSense,这是一个开源的,低成本的平台,用于开发和测试INS算法.
- 在INS中展示使用FreeRTOS和低成本MEMS传感器的可行性.
- 为研究人员提供一个用于验证估计算法的实用工具.
主要方法:
- 在使用FreeRTOS实时操作系统开发INS OpenNavSense.
- 集成低成本传感器:加速度计,陀螺仪,磁力计,GPS和气压计.
- 实施传感器数据校准和过技术.
- 使用开源的Mahony库对态度和标题参考系统 (AHRS) 估计进行验证.
- 与无人机现有的INS进行比较测试.
主要成果:
- 基于FreeRTOS的平台成功地管理了INS的并行处理任务.
- 校准和过的传感器数据提高了低成本系统的准确性.
- 在平台上有效利用Mahony图书馆进行AHRS估计.
- 使用无人机INS进行的比较测试显示了类似的性能,验证了平台的可行性.
结论:
- INS OpenNavSense为INS的研究和开发提供了一个强大的,低成本和可访问的平台.
- 该平台展示了FreeRTOS在使用MEMS传感器管理复杂的导航任务中的有效性.
- 它是研究人员在现实应用中测试和验证新型估计算法的一个有价值的工具.
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