Abstract
We introduce a localization algorithm that uses an inertial measurement unit (IMU) and wheel odometry on a four-wheel-drive heavy vehicle for positioning. While wheel odometry alone works in simple cases without slippage, in cases that feature wheel slippage, the velocities measured by the wheel rotation show higher values. In the case of side slippage, the wheel sensors cannot observe the values. Therefore, IMUs are suitable for fusion with wheel odometry to generate real-time feedback. We use an error state Kalman filter (ESKF) to fuse the sensor information from an IMU with wheel odometry, showing results on a slow-manoeuvring vehicle in tests up to five minutes in length. The IMU is an industry-grade micro-electro mechanical system (MEMS) with a gyroscope featuring 6°/h bias in-run stability. We use a real-time kinematic global positioning system (RTK)-GPS as a ground truth reference for the vehicle’s heading angle and position. The tests results show our navigation has an accuracy of 0.3 m for position and 0.6° for heading angle, both within the root mean square error (RMSE) criteria. Our analysis shows that the nonlinearity of the gyroscope in the heading rotation axis is the key factor for improving performance in our implementation.
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Zhang, X., Liikanen, H., Peltola, E., Aref, M.M., Mattila, J. (2022). Localization of a Heavy-Duty Omnidirectional Vehicle Using IMU and Wheel Odometry. In: Zattoni, E., Simani, S., Conte, G. (eds) 15th European Workshop on Advanced Control and Diagnosis (ACD 2019). ACD 2019 2018. Lecture Notes in Control and Information Sciences - Proceedings. Springer, Cham. https://doi.org/10.1007/978-3-030-85318-1_67
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DOI: https://doi.org/10.1007/978-3-030-85318-1_67
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