无人农场中的智能控制技术应用现状与趋势

doi:10.12398/j.issn.2096-7217.2023.03.001

摘要/Abstract

摘要：

在中国城镇化浪潮下，土地流转也将成为土地高效集约化利用带来契机。未来农业，技术先行，无人农场技术模式是对农业未来的可持续发展进行的一种大胆的尝试与探索。该研究分析自主定位导航技术、在线专业传感器、工作障碍信息感知技术、路径规划决策技术、多机协同技术、自主作业和变量作业等技术的研究应用现状，研判农业大数据、智能决策系统和机器人作业装备等关键核心技术前沿和发展趋势，提出农业智能设备的专用传感器、精准操作决策控制系统、实用的智能设备仍然是无人农场实际应用的关键环节。研究表明无人农场技术模式当前存在基础数据积累不足、环境—作物—装备互作机理不明、智能装备多参数融合调控策略缺乏等重大问题，需要重点关注农业大数据、智能决策系统、机器人操作设备、无人农场领域示范等核心技术，为无人农场农业生产自动化、智能化和环境可持续性的优化发展提供了一定思路。

关键词: 无人农场, 智能控制技术, 农业感知传感器, 智能自主作业

Abstract:

With China’s urbanization， land circulation has emerged as an avenue for efficient and intensive land use. Embracing technology as a primary driver， the unmanned farm technology model represents a bold attempt at sustainable agriculture development. This review focuses on the frontier and development trajectory of key core technologies， and addresses the significant industrial challenges of insufficient accumulation of data on unmanned farms， unknown interaction mechanisms among the environment， plants， and equipment， and lack of multi-parameter integration and regulation strategies for intelligent equipment. Technologies such as autonomous positioning and navigation， online professional sensor， work obstacle information perception， path planning， decision-making， multi-machine collaboration， autonomous operation， and variable operation technology have been implemented in this study. The research shows that， in future， realizing unmanned farms requires special sensors for agricultural intelligent equipment， precise operational decision control systems， and practically intelligent equipment. At meanwhile， addressing such challenges necessitates a focus on core technologies such as insufficient basic big data accumulation of unmanned farms， modeling of environment-plant-equipment interaction mechanism， and intelligent decision control algorithm. This comprehensive improvement in automation， intelligence， and environmental sustainability of agricultural production marks the future development trajectory of unmanned farms.

Key words: unmanned farm, intelligent control technology, agriculture perception sensors, intelligent task automation

中图分类号:

钱震杰, 金诚谦, 刘政, 杨腾祥. 无人农场中的智能控制技术应用现状与趋势[J]. 智能化农业装备学报（中英文）, 2023, 4(3): 1-13.

QIAN Zhenjie, JIN Chengqian, LIU Zheng, YANG Tengxiang. Development status and trends of intelligent control technology in unmanned farms[J]. Journal of Intelligent Agricultural Mechanization, 2023, 4(3): 1-13.

图/表 10

Figure 1 Schematic of unmanned farm systems

Figure 2 Integrated solutions for unmanned farms

Figure 3 Loss rate sensor， impurity content sensor， and yield diagram

Figure 4 Improved Deeplabv3+ with coding layer and attention mechanism optimization

Figure 5 Intelligent soybean sensors and system for combine harvesters

Figure 6 Path planning decisions technolog

Figure 7 Multiple machines cooperative technology

Figure 8 Driverless technology

Figure 9 Agriculture machine with variable operation decision system

Figure 10 Unmanned farm intelligent management platform

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