Navigation system for agricultural machines: Nonlinear Model Predictive path tracking

This article presents a new kind of navigation system for agricultural machines. The focus is on trajectory control where a Nonlinear Model Predictive path tracking for tractor and trailer system is presented. The experiments of the proposed method are carried out by using real agricultural machines in real environments.The agricultural objective is to drive so that swaths are exactly side-by-side, without overlapping or gaps. Hence, the objective of this research was to control the lateral position of the towed implement and to keep it close to the adjacent driving line. The adjacent driving line was recognized locally by using a 2D laser scanner. The local measurement and global position information was merged with the help of an Extended Kalman Filter (EKF). The measurement of the heading by GPS was improved by using an inertial measurement unit and a separate EKF filter. The position of the implement was controlled by steering the tractor and by the use of a hydraulically controlled joint. Because there were two actuators which affected the position of the implement, the problem was a multivariable control problem. Nonlinear Model Predictive Control (NMPC) was used to accomplish the navigation task.The goal was to build a system, which is able to have at least the same accuracy as a human driver. The sufficient accuracy requirement was at most 10 cm lateral error at a speed of 12 km/h. The results presented in the article show that the goal was met and NMPC is a feasible method for accurate path tracking. Further investigation is, however, needed to adapt the method to other kinds of agricultural machines.

► Combined navigation of the tractor and the implement.
► Nonlinear Model Predictive path tracking.
► Local and global position measurement merged with Extended Kalman Filter.
► Variable prediction horizon length.