High-order continuous task planning and tracking control for orchard tracked robots

Abstract Agricultural robots are typically required to operate for extended periods on orchard farms and perform a series of tasks. However, the demands and constraints of these tasks can vary significantly, and smooth transitions between different task states are crucial for improving the continuity and precision of autonomous operations. This paper addresses these challenges for a tracked agricultural robot by (i) deriving a unified kinematic–dynamic model of the platform, (ii) proposing a multi-task motion-planning method that enforces higher-order continuity in position, velocity, acceleration, and jerk, and (iii) designing an optimal tracking controller to follow the planned trajectories under kinodynamic and energy-efficiency considerations. The framework is evaluated through trajectory generation and closed-loop navigation experiments in orchard settings. The controller accurately follows the planned paths, achieving maximum navigation errors of 0.0758 m (lateral) and 0.0810 m (longitudinal), with corresponding root-mean-square errors of 0.0216 m and 0.0169 m. These results indicate that the proposed approach enables smooth, interruption-free transitions between adjacent task states and delivers precise navigation across all operational phases. The method provides a practical foundation for reliable, multi-task autonomous operation of tracked robots in precision agriculture.