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WANG Kelin, E-mail: 2024212017@stu.njau.edu.cn
Outline
Chinese livestock and poultry farming sector consistently ranks among the global leaders in production volume. It not only has a comprehensive range of farming types, but also has a complete industrial chain with associated supporting infrastructure, and occupies a pivotal position in the agricultural industry. In recent years, due to the rapid development of large-scale farming, increased prevalence of animal diseases, persistent labor shortages and other factor shave intensified the demands for intelligent and automated farming equipment. Farming robots, as an important carrier for realizing intelligent agriculture, can effectively replace or assist humans in various tasks, and have great significance and broad prospects for enhancing animal welfare, improving production efficiency, and reducing pollution and waste. This article reviews the application of intelligent technologies such as image recognition, deep learning, reinforcement learning, and autonomous navigation, as well as key components such as thermal infrared cameras, depth cameras, and LiDAR in farming robots, and introduces its achievable functions such as animal physiological information detection, behavior posture recognition, environmental monitoring and control, and feed and milk management. In addition, considering that China’s automated commenced development more recently, there is still a developmental gap compared to some developed countries. Therefore, this article examines the current industrial status and direction of intelligent farming robots both domestically (in China) and internationally, which includes an exploration of its development history, market prospects and policy support. This article also looks forward to the future development of the smart farming industry, points out the challenges of current technologies in terms of economy, stability, animal acceptance, etc., and proposes possible future directions and improvement goals, aiming to provide a reference for relevant researchers to further promote technological innovation and industrial applications.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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