摘 要
随着现代农业向精准化、智能化方向发展，自动驾驶技术在农业机械中的应用日益受到关注。本研究旨在探索农业机械自动驾驶技术的关键问题及其实际应用效果，通过融合多传感器数据与高精度定位系统，设计了一种适用于复杂农田环境的自动驾驶控制算法。研究采用路径规划、障碍物检测及实时决策等方法，构建了完整的农业机械自动驾驶系统，并在多种典型农田场景中进行了试验验证。结果表明，该系统能够实现厘米级定位精度和稳定的路径跟踪性能，显著提升了作业效率与土地利用率。此外，创新性地引入了基于深度学习的障碍物识别模块，有效解决了传统方法在复杂环境下的适应性不足问题。研究表明，农业机械自动驾驶技术不仅可降低人工成本，还为智慧农业的发展提供了重要技术支持，具有广阔的应用前景。
关键词：农业机械自动驾驶；多传感器融合；路径规划；深度学习障碍物识别；农田场景应用
RESEARCH AND APPLICATION OF AUTONOMOUS DRIVING TECHNOLOGY FOR AGRICULTURAL MACHINERY
ABSTRACT
With the development of modern agriculture towards precision and intelligence, the application of autonomous driving technology in agricultural machinery has gained increasing attention. This study aims to explore the key issues of autonomous driving technology for agricultural machinery and its practical application effects, designing an autonomous driving control algorithm suitable for complex farmland environments by integrating multi-sensor data with high-precision positioning systems. The research employs methods such as path planning, obstacle detection, and real-time decision-making to construct a complete autonomous driving system for agricultural machinery, which was experimentally validated across various typical farmland scenarios. The results demonstrate that the system achieves centimeter-level positioning accuracy and stable path tracking performance, significantly enhancing operational efficiency and land utilization. Additionally, an innovative obstacle recognition module based on deep learning was introduced, effectively addressing the adaptability limitations of traditional methods in complex environments. The study indicates that autonomous driving technology for agricultural machinery not only reduces labor costs but also provides crucial technical support for the development of smart agriculture, showcasing broad application prospects.
KEY WORDS：Agricultural Machinery Autonomous Driving；Multi-Sensor Fusion；Path Planning；Deep Learning Obstacle Recognition；Farmland Scene Application
目 录
摘 要 I
ABSTRACT II
第一章 绪论 1
1.1 农业机械自动驾驶技术的研究背景 1
1.2 国内外研究现状与发展趋势 1
第二章 自动驾驶关键技术分析 1
2.1 导航与定位技术的应用研究 2
2.2 传感器融合技术的实现路径 2
2.3 控制算法在农业机械中的优化 3
第三章 农业场景下的应用挑战 3
3.1 复杂地形对自动驾驶的影响 3
3.2 气候因素对系统性能的要求 4
3.3 数据采集与处理的技术难点 4
第四章 系统设计与实验验证 5
4.1 自动驾驶系统的架构设计 5
4.2 实验平台搭建与测试方法 5
4.3 实验结果分析与性能评估 6
结 论 6
参考文献 7
致 谢 8
