选择性收获机器人技术研究进展与分析
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国家自然科学基金项目(51675317)


Research Progress Analysis of Robotics Selective Harvesting Technologies
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    摘要:

    鲜食果蔬成熟度不一致,需依据着色、尺寸等指标有选择地收获,是人工消耗最大、影响产业发展的瓶颈环节。选择性收获技术是农业机器人的重要研究领域,能降低人工成本并提高果蔬利润,已成为国际上果蔬收获技术发展的重要方向。近年来,以白芦笋为代表等地下部和苹果、草莓、番茄等为代表地上部的鲜食果蔬选择性收获技术进展加快,成为农业机器人的研究热点。本文阐述了近年具有市场化前景的选择性收获技术发展与应用情况,梳理出技术研发的实现路径、应用对象和发展脉络。着重分析了末端执行器与收获机构、收获目标识别与定位技术、选择性收获协同控制技术的共性关键问题,归纳了该领域技术研究的开放性问题。最后,总结了我国选择性收获技术面临的挑战和机遇,针对少人化或无人化果蔬生产的应用场景,指出了产业未来发展与技术产品化需考虑的平衡点。

    Abstract:

    The maturity of fresh fruits and vegetables is inconsistent, requiring selective harvesting based on indicators such as color and size, which consumes the most labor and becomes a bottleneck affecting the development of the fruit and vegetable industry. Selective harvesting technology (SHT) is an important research field of agricultural robots, which can reduce labor costs and increase fruit and vegetable profits, and has become an important direction for the development of fruit and vegetable harvesting technology in the world. The SHT of fresh fruits and vegetables, including the representative underground parts such as white asparagus and the representative aerial parts such as apples, strawberries, tomatoes, has accelerated iteratively and has become a research hotspot of agricultural robots in recent years. It focused on the development of SHT with market-oriented prospects in the past three years, and sorted out the implementation path, application objects and development context of technology research and development. It focused on the common key issues of end effector and harvesting mechanism, harvesting target recognition and positioning technology, and selective harvesting collaborative control technology, and summarized the open problem of technical research in this field. Finally, it summarized the challenges and opportunities faced by SHT. Aiming at the application scenarios of dehumanized or unmanned fruit and vegetable production, it pointed out that the future development of the industry and the implementation of technology needed to be balanced.

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苑进.选择性收获机器人技术研究进展与分析[J].农业机械学报,2020,51(9):1-17. YUAN Jin. Research Progress Analysis of Robotics Selective Harvesting Technologies[J]. Transactions of the Chinese Society for Agricultural Machinery,2020,51(9):1-17.

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  • 收稿日期:2020-07-30
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  • 在线发布日期: 2020-09-10
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