Real-time slip angle estimation in off-road vehicles using GNSS and IMU integration

Abstract

This thesis presents a method for real-time estimation of body slip angle in off-road vehicles using integrated Global Navigation Satellite System (GNSS) and Inertial Measurement Unit (IMU) data. Slip angle, defined as the angular difference between a vehicle’s heading and its actual trajectory, is a critical parameter for vehicle stability, navigation, and tyre performance assessment. Conventional methods rely on steering angle sensors or vision-based sensors, which often perform inadequately in off-road conditions due to terrain variability, low traction, and ground conditions.

The proposed solution fuses IMU data with GNSS-based information through Kalman filtering. The estimation algorithm integrates yaw rate, game rotation vector, and GNSS- derived heading to determine vehicle orientation and direction of motion. Drift correction mechanisms and sensor synchronization techniques are employed to ensure robust performance in low-speed and high-slip environments.

Experimental validation was conducted on both a road vehicle and a tyre testing trailer equipped with dual GNSS antennas and a 9-DOF IMU. The results demonstrate that the slip angle estimation is suitable for applications in autonomous agricultural machinery and dynamic tyre testing platforms. This system improves vehicle state awareness and enhances navigation reliability in unstructured environments.