论文标题
Wheel-ins2：多个MEMS IMU的DEAD RECKONING WORED ROBOTS，并评估不同的IMU配置
Wheel-INS2: Multiple MEMS IMU-based Dead Reckoning System for Wheeled Robots with Evaluation of Different IMU Configurations
论文作者
论文摘要
可靠的独立导航系统对于自动驾驶汽车至关重要。基于我们先前关于车轮\ cit {niu2019}的研究，这是一个由车轮安装的惯性测量单元（Wheel-imu）基于车轮的死亡计算（DR）系统，在本文中，我们为轮式机器人提出了多个基于IMUS的DR解决方案。 IMU被安装在轮式车辆的不同位置，以获取各种动态信息。特别是，必须将至少一个IMU安装在车轮上以测量车轮速度并具有旋转调制的优势。该系统是通过分布式扩展的Kalman滤波器结构实现的，每个子系统（对应于每个IMU）将分别保留和更新其自己的状态。利用多个IMU之间的相对位置约束，以进一步限制误差漂移并改善系统鲁棒性。特别是，我们使用双轮imus，一个轮子IMU加上车身安装的IMU（Body-IMU）和双轮IMU以及一个Body-IMU作为分析和比较的示例。现场测试表明，所提出的多IMU DR系统在定位和标题准确性方面优于单轮的表现。通过与集中级过滤器进行比较，提出的分布式滤波器显示出不重要的精度降解，而具有显着的计算效率。此外，在三种多IMU配置中，一个Body-IMU和一个Wheel-IMU设计可获得最小的漂移速率。这三个配置的位置漂移速率分别为0.82 \％（双轮imus），0.69 \％（一个Body-Imu加一个轮子IMU）和0.73 \％（双轮imimus和一个车身IMU）。
A reliable self-contained navigation system is essential for autonomous vehicles. Based on our previous study on Wheel-INS \cite{niu2019}, a wheel-mounted inertial measurement unit (Wheel-IMU)-based dead reckoning (DR) system, in this paper, we propose a multiple IMUs-based DR solution for the wheeled robots. The IMUs are mounted at different places of the wheeled vehicles to acquire various dynamic information. In particular, at least one IMU has to be mounted at the wheel to measure the wheel velocity and take advantages of the rotation modulation. The system is implemented through a distributed extended Kalman filter structure where each subsystem (corresponding to each IMU) retains and updates its own states separately. The relative position constraints between the multiple IMUs are exploited to further limit the error drift and improve the system robustness. Particularly, we present the DR systems using dual Wheel-IMUs, one Wheel-IMU plus one vehicle body-mounted IMU (Body-IMU), and dual Wheel-IMUs plus one Body-IMU as examples for analysis and comparison. Field tests illustrate that the proposed multi-IMU DR system outperforms the single Wheel-INS in terms of both positioning and heading accuracy. By comparing with the centralized filter, the proposed distributed filter shows unimportant accuracy degradation while holds significant computation efficiency. Moreover, among the three multi-IMU configurations, the one Body-IMU plus one Wheel-IMU design obtains the minimum drift rate. The position drift rates of the three configurations are 0.82\% (dual Wheel-IMUs), 0.69\% (one Body-IMU plus one Wheel-IMU), and 0.73\% (dual Wheel-IMUs plus one Body-IMU), respectively.
