Global–local integrated path planning strategy for agricultural robots in complex hilly orchard environments

Hilly orchards, which account for over 60% of China’s orchard area, present complex terrain that limits the effectiveness of conventional agricultural machinery, resulting in high labor requirements and low operational efficiency. Agricultural robots offer a promising solution, with path planning as a critical enabling technology. However, existing methods often suffer from limited terrain adaptability, inadequate obstacle avoidance, poor dynamic responsiveness, and compromised operational safety. To address these challenges, this study proposes a dual closed-loop global–local path planning framework for orchard robots operating in hilly environments. A terrain-aware traffic cost model and a slip-inclusive kinematic model are first developed to characterize traversability and motion stability. Building on these models, the A* algorithm is enhanced for global path planning, while the Dynamic Window Approach (DWA) is improved to enable local obstacle avoidance while satisfying terrain stability constraints. A double closed-loop control architecture integrates global path constraints with local environmental feedback and real-time replanning, achieving a balance between global optimality and local responsiveness. Field experiments demonstrate that the proposed strategy reduces path length by 2.1–19.8% and slip ratio by 2.7–8.0% compared with conventional methods, achieves a 100% obstacle-avoidance success rate, and maintains lateral trajectory deviations below 15.2 cm. These results validate the method as a safe, stable, and efficient approach for robotic operations in hilly orchards, highlighting its potential for practical deployment in complex agricultural environments.