Research on Road Slope Estimation and the Passable Area Modelling Method in Hilly and Mountainous Areas Based on Multi-Sensor Fusion

Autonomous tractors have been shown to possess the capability to ensure a high degree of operational precision during seeding activities on flat terrain. However, in topographically challenging environments characterised by significant elevations and pronounced variations in slope, factors such as road gradients have been shown to compromise the precision of satellite-based positioning systems. This, in turn, can lead to alterations in vehicle posture and the generation of disparate longitudinal driving forces between the left and right tyres. It is important to note that this deviation from the predefined path has the potential to result in rollover accidents. Evidence has been presented that indicates a correlation between road gradient and vehicle roll motion. The proposed methodology is an algorithmic approach to the estimation of lateral slope, integrating inertial measurement unit (IMU) sensors and ground-based ultrasonic radars. This algorithmic approach is proposed as a means to achieve more accurate estimations of lateral slope. The initial development of the vehicle dynamics model was based on slope operation requirements, and the model was endowed with eight degrees of freedom. The utilisation of an unscented Kalman filter (UKF) facilitates the integration of inertial measurement unit (IMU) and ground-based ultrasonic radar measurements, thereby enabling real-time estimation of key motion states, such as lateral slope. The validity of the proposed algorithm was established through a combination of hardware-in-the-loop testing and field trials involving real tractors. The findings indicate that the implementation of this algorithm leads to a substantial enhancement in the trajectory tracking accuracy of tractors during slope operations. This enhancement is characterised by a substantial reduction in lateral deviation and an effective augmentation in the operational pass rate. In the course of empirical trials conducted in a mountainous environment, the lateral positioning deviation during straight-line driving was diminished from 10 cm to within 5 cm. Concurrently, the precision of lateral slope estimation was enhanced to 0.04 degrees.