为果园农机转向设计高效安全的轨迹规划算法
Efficient and Safe Trajectory Planning for Autonomous Agricultural Vehicle Headland Turning in Cluttered Orchard Environments
- 结合自动驾驶技术，分前后端优化转向路径
- 在复杂果园中比现有方法更安全高效
- 适合需要精细作业的智能农机研发人员
自主农业车辆（AAVs）如田间机器人和自动驾驶拖拉机正成为现代农耕的重要工具，可提升效率并降低人力成本。在作物行间进行头地转向是其关键任务，但在头地空间有限、边界不规则、存在静态障碍且受操作约束的果园环境中极具挑战。传统轨迹规划方法在大田作业中表现良好，却难以适应复杂果园场景。本文提出一种新型轨迹规划器，通过先进自动驾驶技术提升农机头地转向的安全性与效率。该方法包含高效的前端算法和高性能后端优化，适用于配备多种作业装置的车辆，在标准及复杂果园场景中均优于当前最优方法。本研究推动了农业与自动驾驶技术的融合，助力智能农机在复杂果园环境中的广泛应用。
原文摘要 · Abstract (English)
Autonomous agricultural vehicles (AAVs), including field robots and autonomous tractors, are becoming essential in modern farming by improving efficiency and reducing labor costs. A critical task in AAV operations is headland turning between crop rows. This task is challenging in orchards with limited headland space, irregular boundaries, operational constraints, and static obstacles. While traditional trajectory planning methods work well in arable farming, they often fail in cluttered orchard environments. This letter presents a novel trajectory planner that enhances the safety and efficiency of AAV headland maneuvers, leveraging advancements in autonomous driving. Our approach includes an efficient front-end algorithm and a high-performance back-end optimization. Applied to vehicles with various implements, it outperforms state-of-the-art methods in both standard and challenging orchard fields. This work bridges agricultural and autonomous driving technologies, facilitating a broader adoption of AAVs in complex orchards.
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