智能农机具的自主导航与避障技术研究
摘 要
随着农业现代化进程的加速，智能农机具的自主导航与避障技术成为提升农业生产效率的关键。本研究旨在解决传统农机具在复杂农田环境中导航精度低、避障能力不足的问题，通过融合多传感器数据与深度学习算法，提出了一种新型自主导航与避障系统。研究采用激光雷达、视觉传感器和惯性测量单元（IMU）等多源数据融合技术，构建了高精度的环境感知模型；同时，基于改进的深度强化学习算法，设计了自适应路径规划与动态避障策略。实验结果表明，该系统在多种农田场景下的导航精度达到厘米级，避障成功率超过95%，显著优于传统方法。此外，研究还开发了一套适用于中国典型农田环境的智能农机具原型机，并在江苏、山东等地进行了实地测试，验证了系统的实用性与可靠性。
关键词：智能农机具；自主导航；避障技术
RESEARCH ON AUTONOMOUS NAVIGATION AND OBSTACLE AVOIDANCE TECHNOLOGY OF INTELLIGENT AGRICULTURAL MACHINERY AND TOOLS
ABSTRACT
With the acceleration of agricultural modernization process, the independent navigation and obstacle avoidance technology of intelligent agricultural machinery and tools have become the key to improve the efficiency of agricultural production. This study aims to solve the problems of low navigation accuracy and insufficient obstacle avoidance ability of traditional agricultural machinery and tools in complex farmland environment, and proposes a new autonomous navigation and obstacle avoidance system by integrating multi-sensor data and deep learning algorithm. Multi-source data fusion technology such as lidar, visual sensor and inertial measurement unit (IMU) is used to build high-precision environment perception model. Meanwhile, the adaptive path planning and dynamic obstacle avoidance strategy are designed based on improved deep reinforcement learning algorithm. The experimental results show that the navigation accuracy of the proposed system reaches centimeter level, and the success rate of obstacle avoidance exceeds 95%, which is significantly better than the conventional methods. In addition, the research also developed a set of intelligent agricultural machinery prototype suitable for the typical farmland environment in China, and conducted field tests in Jiangsu, Shandong and other places to verify the practicability and reliability of the system.
KEY WORDS：Intelligent agricultural machinery and tools; autonomous navigation; obstacle avoidance technology
目 录
摘 要 I
ABSTRACT II
第1章 绪论 1
1.1 研究背景及意义 1
1.2 研究目的和内容 1
第2章 智能农机具自主导航技术研究 2
2.1 自主导航系统架构设计 2
2.2 定位与路径规划算法 2
2.3 导航精度优化方法 3
第3章 智能农机具避障技术研究 4
3.1 障碍物检测与识别技术 4
3.2 避障决策与控制策略 4
3.3 多传感器融合避障系统 5
第4章 智能农机具导航与避障集成应用 6
4.1 导航与避障系统集成设计 6
4.2 田间作业场景适应性分析 6
4.3 系统性能测试与评估 7
第5章 结论 8
参考文献 9
致 谢 10
摘 要
随着农业现代化进程的加速，智能农机具的自主导航与避障技术成为提升农业生产效率的关键。本研究旨在解决传统农机具在复杂农田环境中导航精度低、避障能力不足的问题，通过融合多传感器数据与深度学习算法，提出了一种新型自主导航与避障系统。研究采用激光雷达、视觉传感器和惯性测量单元（IMU）等多源数据融合技术，构建了高精度的环境感知模型；同时，基于改进的深度强化学习算法，设计了自适应路径规划与动态避障策略。实验结果表明，该系统在多种农田场景下的导航精度达到厘米级，避障成功率超过95%，显著优于传统方法。此外，研究还开发了一套适用于中国典型农田环境的智能农机具原型机，并在江苏、山东等地进行了实地测试，验证了系统的实用性与可靠性。
关键词：智能农机具；自主导航；避障技术
RESEARCH ON AUTONOMOUS NAVIGATION AND OBSTACLE AVOIDANCE TECHNOLOGY OF INTELLIGENT AGRICULTURAL MACHINERY AND TOOLS
ABSTRACT
With the acceleration of agricultural modernization process, the independent navigation and obstacle avoidance technology of intelligent agricultural machinery and tools have become the key to improve the efficiency of agricultural production. This study aims to solve the problems of low navigation accuracy and insufficient obstacle avoidance ability of traditional agricultural machinery and tools in complex farmland environment, and proposes a new autonomous navigation and obstacle avoidance system by integrating multi-sensor data and deep learning algorithm. Multi-source data fusion technology such as lidar, visual sensor and inertial measurement unit (IMU) is used to build high-precision environment perception model. Meanwhile, the adaptive path planning and dynamic obstacle avoidance strategy are designed based on improved deep reinforcement learning algorithm. The experimental results show that the navigation accuracy of the proposed system reaches centimeter level, and the success rate of obstacle avoidance exceeds 95%, which is significantly better than the conventional methods. In addition, the research also developed a set of intelligent agricultural machinery prototype suitable for the typical farmland environment in China, and conducted field tests in Jiangsu, Shandong and other places to verify the practicability and reliability of the system.
KEY WORDS：Intelligent agricultural machinery and tools; autonomous navigation; obstacle avoidance technology
目 录
摘 要 I
ABSTRACT II
第1章 绪论 1
1.1 研究背景及意义 1
1.2 研究目的和内容 1
第2章 智能农机具自主导航技术研究 2
2.1 自主导航系统架构设计 2
2.2 定位与路径规划算法 2
2.3 导航精度优化方法 3
第3章 智能农机具避障技术研究 4
3.1 障碍物检测与识别技术 4
3.2 避障决策与控制策略 4
3.3 多传感器融合避障系统 5
第4章 智能农机具导航与避障集成应用 6
4.1 导航与避障系统集成设计 6
4.2 田间作业场景适应性分析 6
4.3 系统性能测试与评估 7
第5章 结论 8
参考文献 9
致 谢 10
