Our team member Ngoc Thinh Nguyen travelled to Japan to present new results about our project at this year’s prestigious ICRA conference.

Navigating through agricultural fields presents unique challenges that demand exceptional manoeuvrability. One promising solution is the use of four-wheel steering (4WS) vehicles, which can switch between various steering mechanisms, each with distinct kinematic properties tailored for specific tasks.

For instance, the parallel positive steering (PPS) mode aligns all four wheels parallel to each other, allowing the vehicle to maintain its heading while moving along a curve. On the other hand, symmetric negative steering (SNS) mode, where each pair of wheels on either side share the same steering angle, enables the vehicle to turn with a minimal radius.

In our latest research, we introduce an innovative controller that autonomously selects and switches between these two steering modes, significantly enhancing trajectory tracking performance under specific heading requirements crucial for agricultural applications. This controller is designed as a Model Predictive Control (MPC) system and formulated as a mixed-integer quadratic programming (MIQP) problem specifically for 4WS vehicles.

Our approach accounts for practical constraints, such as limits on wheel velocities, steering angles, and their rate of change. Implemented in Python, our controller has been demonstrated to execute in real-time. Simulation results further underscore its effectiveness in navigating complex agricultural environments.

Stay tuned for more insights on how advanced steering technologies are revolutionizing agricultural field operations, ensuring precision and efficiency in every move.