It is essential that a robot has the ability to determine its position and orientation to execute tasks autonomously. Heading estimation is especially challenging in indoor environments where magnetic distortions make magnetometer-based heading estimation difficult. Ultra-wideband (UWB) transceivers are common in indoor localization problems. This letter experimentally demonstrates how to use UWB range and received signal strength (RSS) measurements to estimate robot heading. The RSS of a UWB antenna varies with its orientation. As such, a Gaussian process (GP) is used to learn a data-driven relationship from UWB range and RSS inputs to orientation outputs. Combined with a gyroscope in an invariant extended Kalman filter, this realizes a heading estimation method that uses only UWB and gyroscope measurements.
翻译:至关重要的是,机器人必须有能力自行确定自己的位置和任务执行方向。在磁扭曲导致磁强计标题估计困难的室内环境中,标题估计尤其具有挑战性。超大波段(UWB)收发器在室内本地化问题中很常见。这封信试验性地展示了如何使用UWB射程和接收信号强度(RSS)测量来估计机器人方向。UWB天线的RSS与其方向不同。因此,Gossian进程(GP)用来学习从UWB射程和RSS输入到定向输出的数据驱动关系。这与一个变异的扩展的Kalman过滤器中的陀螺仪相结合,实现了一种仅使用UWB和陀螺仪测量的航标估计方法。