NR5G-SAM:基于5G新无线电的现场机器人应用的SLAM框架
Panagiotis T Karfakis1,2, Micael S Couceiro1,2, David Portugal2
1Ingeniarius Ltd., R. Nossa Sra. Conceição 146, 4445-147 Alfena, Portugal.
Sensors (Basel, Switzerland)
|June 10, 2023
概括
本研究介绍了一种基于5G新无线电 (NR) 的蜂同步定位和映射 (SLAM) 框架,用于机器人定位. 它为全球导航卫星系统 (GNSS) 和LiDAR方法提供了一个强大的替代方案,用于挑战户外环境.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 无线通信无线通信
- 传感器融合式传感器
背景情况:
- 机器人定位对于导航至关重要,但在城市/农村地区面临全球导航卫星系统 (GNSS) 的局限性.
- 激光雷达,惯性和视觉方法容易发生漂移和环境/照明条件变化.
- 现有的本地化技术在各种户外场景中往往缺乏稳定性.
研究的目的:
- 为移动机器人定位提出一个新的蜂同步定位和映射 (SLAM) 框架.
- 为了利用5G新无线电 (NR) 信号和惯性测量,提高定位精度.
- 使用接收信号强度指标 (RSSI) 创建无线电信号地图以进行姿势校正.
主要方法:
- 开发了一个蜂SLAM框架,集成5G NR信号和惯性测量单元 (IMU).
- 使用gNodeB站进行信号三角化和收到信号强度指标 (RSSI) 映射.
- 通过使用模拟器和现实世界的实验,对拟议的方法与LiDAR-Inertial Odometry Smoothing and Mapping (LIO-SAM) 进行了基准测试.
- 在使用下链 (DL) 信号的6GHz以下和毫米波频段的评估性能.
主要成果:
- 基于5G的蜂SLAM框架在户外环境中表现出更高的稳定性.
- 该系统成功生成了用于姿势校正的无线电信号地图.
- 性能与最先进的LiDAR SLAM方法进行了验证.
- 拟议的方法显示了作为补充绝对定位源的潜力.
结论:
- 对于无线电SLAM,5G定位是可行的,增强机器人定位能力.
- 当GNSS无法使用或LiDAR/IMU方法退化时,该框架提供了可靠的替代方案.
- 这种方法为户外环境中的移动机器人提供了更好的稳定性和准确性.
关键词:
5G NR 5G NR是5G网络中的一个.在REM中,REM是REM.斯拉姆斯兰姆斯兰姆斯兰姆斯兰姆斯兰姆斯兰姆斯兰姆斯兰姆斯兰姆斯现场机器人领域 机器人领域这就是iSAM.构成估计估计的估计.无线电地图绘制 无线电地图绘制融合传感器 融合传感器 融合传感器更多相关视频
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