From Theory to Practice: Identifying the Optimal Approach for Offset Point Tracking in the Context of Agricultural Robotics

Modern agriculture faces escalating challenges: increasing demand for food, labor shortages, and the urgent need to reduce environmental impact. Agricultural robotics has emerged as a promising response to these pressures, enabling the automation of precise and suitable field operations. In particular, robots equipped with implements for tasks such as weeding or sowing must interact delicately and accurately with the crops and soil. Unlike robots in other domains, these agricultural platforms typically use rigidly mounted implements, where the implement's position is more critical than the robot's center in determining task success. Yet, most control strategies in the literature focus on the vehicle body, often neglecting the acctual working point of the system. This is particularly important when considering new agriculture practices where crops row are not necessary straights. This paper presents a predictive control strategy targeting the implement's reference point. The method improves tracking performance by anticipating the motion of the implement, which, due to its offset from the vehicle's center of rotation, is prone to overshooting during turns if not properly accounted for.