Wheel-INS2: Multiple MEMS IMU-based Dead Reckoning System for Wheeled Robots with Evaluation of Different IMU Configurations
This research provides an incremental improvement in dead reckoning accuracy for autonomous wheeled robots, which is crucial for their reliable self-contained navigation.
This paper proposes Wheel-INS2, a multiple MEMS IMU-based dead reckoning system for wheeled robots, building on the previous Wheel-INS. The system uses a distributed extended Kalman filter and exploits relative position constraints between IMUs to improve accuracy. The best configuration (one Body-IMU plus one Wheel-IMU) achieved a position drift rate of 0.69%, outperforming single Wheel-INS and other multi-IMU configurations.
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.