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[学术文献 ] Cyber-agricultural systems for crop breeding and sustainable production 进入全文
TRENDS IN PLANT SCIENCE
网络农业系统（CAS）代表了农业的总体框架，它利用了育种和农业生产中无处不在的传感、人工智能、智能执行器和可扩展网络基础设施（CI）的最新进展。我们讨论了CAS的三个基本组成部分——传感、建模和驱动的最新进展和前景，以及新兴的农业数字孪生（DTs）概念。我们还讨论了可扩展的CI如何成为智能农业的关键推动者。在这篇综述中，我们阐明了CAS通过提高效率、生产力、可持续性和对气候变化的适应能力来革新作物育种和生产的重要意义。最后，我们确定了CAS研究和发展的未充分探索和有希望的未来方向。
[学术文献 ] Digital twins in smart farming: An autoware-based simulator for autonomous agricultural vehicles 进入全文
INTERNATIONAL JOURNAL OF AGRICULTURAL AND BIOLOGICAL ENGINEERING
Digital twins can improve the level of control over physical entities and help manage complex systems by integrating a range of technologies. The autonomous agricultural machine has shown revolutionary effects on labor reduction and utilization rate in field works. Autonomous vehicles in precision agriculture have the potential to improve competitiveness compared to current crop production methods and have become a research hotspot. However, the development time and resources required in experiments have limited the research in this area. Simulation tools in unmanned farming that are required to enable more efficient, reliable, and safe autonomy are increasingly demanding. Inspired by the recent development of an open-source virtual simulation platform, this study proposed an autoware-based simulator to evaluate the performance of agricultural machine guidance based on digital twins. Oblique photogrammetry using drones is used to construct three-dimensional maps of fields at the same scale as reality. A communication format suitable for agricultural machines was developed for data input and output, along with an inter-node communication methodology. The conversion, publishing, and maintenance of multiple coordinate systems were completed based on ROS (Robot Operating System). Coverage path planning was performed using hybrid curves based on Bézier curves, and it was tested in both a simulation environment and actual fields with the aid of Pure Pursuit algorithms and PID controllers.
[学术文献 ] A survey on the 5G network and its impact on agriculture: Challenges and opportunities 进入全文
Computers and Electronics in Agriculture
在未来十年，超高速5G网络将在农业中发挥关键作用，在使用最少劳动力的情况下提高作物的产量和质量。智能精准农业使农民获得更多信息和生产力。5G的出现将极大地改变农业和农业工作的性质。5G网络中基于物联网的云计算服务，为智慧农业提供灵活高效的解决方案。这将使各种无人农业机械在作物种植的耕种、种植和管理阶段实现自动化操作，并最终实现安全、可靠、环保和节能的操作，实现无人农场。本文对农业领域的5G技术进行了全面的调查，并讨论了智能精准农业的需求和作用；5G的好处；5G在精准农业中的应用，如实时监控、虚拟咨询和预测性维护、数据分析和云存储库；以及未来前景。
[学术文献 ] 陆地巡检机器人关键技术及其在水产养殖中的应用前景 进入全文
农业工程学报
将陆地巡检技术引入水产养殖工厂可有效解决传统养殖模式低效率、错漏检的关键问题。该文综述了陆地巡检机器人的关键技术及在水产养殖中的应用前景，介绍陆地巡检机器人的定义及其应用发展趋势，重点探讨陆地巡检机器人的关键技术：包括传感器技术、机械驱动技术以及控制技术，详细讨论这些技术的分类、应用、挑战与趋势，进而分析水产养殖陆地巡检机器人的特定应用及技术适配，最后根据使用环境进行水产养殖陆地巡检机器人的技术预测，并根据未来发展挑战提出合理建议。未来水产养殖行业将向无人化巡检养殖发展，通过多传感器实现信息交融，通过交互平台实现远程观测控制，以应对未来复杂水产养殖环境下的数据融合处理，高效率高准确率巡检的挑战。
[学术文献 ] A Review on the High-Efficiency Detection and Precision Positioning Technology Application of Agricultural Robots 进入全文
Processes
农业技术的进步使机器人检测和定位技术日益处于前沿，通过其准确性和可靠性确保了对农业发展的关键支持。本文深入分析了用于检测和定位的各种方法，包括超宽带、深度学习、SLAM和多传感器融合。在检测领域，讨论了深度算法在作物成熟度评估和病虫害分析中的应用。针对定位问题，考察了不同定位方法的精度。此外，还回顾了卷积神经网络和基于深度算法的多传感器融合在农业中的应用。现有方法有效地缓解了环境干扰，显著提高了农业机器人的精度和可靠性。本研究为农业机器人检测与定位的发展提供了方向性的见解，明确了该领域的未来发展轨迹，促进了相关技术的进步。
[学术文献 ] Development and trends of chicken farming robots in chicken farming tasks: A review 进入全文
COMPUTERS AND ELECTRONICS IN AGRICULTURE；
Chicken farming plays a crucial role in the chicken industry. As the market demand for chicken products continues to grow, chicken farming is expanding on a larger scale to meet production needs. To address the challenges posed by the increased workload and labor shortages in chicken farming, chicken farming is transitioning towards standardization, automation, and intelligence. The rapid development of mobile robot technology offers solutions for the automated and intelligent execution of tasks in various scenarios. The automated and intelligent execution of farming tasks by robots holds significant importance in terms of liberating labor, implementing standardization and stable production, ensuring animal welfare, and enhancing production efficiency. In this review, the current situation in the chicken industry and the challenges encountered in implementing automation and intelligence in chicken farming tasks have been summarized to fully illustrate the important role of robots in the automation and intelligence of chicken farming. Based on the proposed categorization that considers the generality of robot technology, we review the application of general-purpose robotic technologies in chicken farming, such as localization, mapping, path planning, control, and interaction technology. Additionally, we explore the development of task-specific robotic technologies for various chicken farming tasks, including inspection, dead chicken picking, chicken house cleaning, and floor egg picking. Some tables are used to record and summarize certain technologies. We have identified that there are still many challenges to overcome in order to achieve mature and stable operation of robots in chicken farming. These challenges include significant technology homogeneity and a lack of attention to the characteristics of scenes and objects in chicken farming environments. To ultimately achieve the goal of an intelligent unmanned chicken farming system, future research priorities and development trends have been highlighted.
