[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-522":3,"related-522":82},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":9,"source_name":10,"source_url":8,"published_at":11,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":15,"score_detail":16,"sources":24,"tags":26,"primary_topic":32,"secondary_topics":38,"classification":39,"search_phrases":77,"slug":80,"view_count":60,"doi":8,"paper":8,"created_at":81},522,"科技日报:山西晋字号农业机器人加速田间应用,智慧农业行动计划落地","https:\u002F\u002Fwww.thepaper.cn\u002FnewsDetail_forward_33781956","科技日报报道,大地智牛机器人填补丘陵山区覆膜播种空白,黄花菜智能采摘机器人投入大田试验,西红柿采摘机器人实测效果显著。山西2025年11月出台山西省智慧农业行动计划(2026—2030年),划定杂粮、设施果蔬、林果、畜禽四大机器人攻关赛道,山西七成耕地为丘陵山地,推动以机适地。每年安排2300余万元省级财政资金扶持建成57个智慧农机社会化服务中心。",null,"坐落于“晋创谷·农高区”的山西农芯硅谷科技有限公司，研发了西红柿采摘机器人和畜牧巡检机器人。其中，西红柿采摘机器人研发团队攻克温室作业难题，实现机械臂轻量化改造，将臂体减重30%—50%，使之适配大棚窄垄环境。畜牧巡检机器人配置多种场景感知摄像头、感知传感器，拥有AI识别和自动决策功能，能够全天候在羊舍巡检，同步采集牲畜体征、采食状况与圈舍环境数据，保障畜禽健康，减少养殖风险。“依托多学科协同攻关，我们打通技术研发与农业场景落地通道，手握十余项核心专利。”山西农芯硅谷科技有限公司负责人胡伯平介绍，企业还针对向日葵产业短板，攻关专用采收机器人。\n\n山西省农业农村厅相关负责人介绍，下一步，山西将持续强化政策扶持，围绕丘陵山地机械化、设施农业智能化、特色作物采收自动化等关键场景持续发力，推动更多农业机器人走出实验室、走进田间厂房，为丘陵山区农业现代化与乡村振兴贡献“山西方案”。","科技日报","2026-08-14T03:43:00Z","报道",10,false,69,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":23},18,16,14,12,9,1,"省级智慧农业进展，含具体技术细节，央媒报道，时效性好。",[25],{"name":10,"url":6},[27,28,29,30,31],"农业机器人","山西","丘陵山区","黄花菜","智慧农业行动计划",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},"F6","agricultural-robots","机器人与无人农场","\u002Ftopic\u002Finputs-equipment\u002Fagricultural-robots","F",[],{"status":40,"locked":14,"version":41,"method":42,"evidence":43},"classified","2026-10-22.2","rules",{"candidates":44,"agricultural_evidence":46},[45,51,58,65,71],{"code":33,"score":20,"supported":46,"title":47,"abstract":48,"tags":50},true,[27],[49],"采摘机器人",[27],{"code":52,"score":53,"supported":46,"title":54,"abstract":56,"tags":57},"I1",11,[55],"智慧农业",[55],[],{"code":59,"score":60,"supported":46,"title":61,"abstract":62,"tags":64},"C",3,[],[63],"畜禽",[],{"code":66,"score":60,"supported":46,"title":67,"abstract":68,"tags":70},"F5",[],[69],"农机",[],{"code":72,"score":60,"supported":46,"title":73,"abstract":74,"tags":76},"G2",[],[75],"社会化服务",[],[78,79],"智慧农业行动计划 农业机器人 丘陵山区 黄花菜","智慧农业行动计划 农业机器人","智慧农业行动计划农业机器人丘陵山区黄花菜-522","2026-08-15T00:02:52.900602Z",{"total":83,"page":22,"page_size":83,"items":84},6,[85,119,168,232,302,359],{"id":86,"title":87,"url":88,"summary":89,"summary_zh":8,"content":90,"source_name":91,"source_url":8,"published_at":92,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":93,"score_detail":94,"sources":100,"tags":102,"primary_topic":104,"secondary_topics":105,"classification":106,"search_phrases":113,"slug":116,"view_count":117,"doi":8,"paper":8,"created_at":118},458,"山西大同黄花菜智能采摘机器人首款田间实操——单次采摘过程不到5秒钟,实现采收'无机可用'到'真机下地'","https:\u002F\u002Fwww.cnr.cn\u002Fsx\u002Frwft\u002F20260810\u002Ft20260810_527756118.shtml","央广网大同8月10日消息:近日,山西大同云州区坨坊村黄花种植基地内,首款黄花菜智能采摘机器人接到种植户下达的采摘指令后,专用手爪精准采收黄花并收纳至储料筐,单次采摘过程不到5秒钟。受作业精度限制,机器人采用分区采收模式,单次定点采摘面积为4平方米。'黄花菜智能采摘机器人关键技术研究及应用示范'项目于2023年获批为山西省重点研发计划项目,由太原科技大学牵头,联合山西农谷现代农业装备科技有限公司、山西农业大学等单位协同攻关。机器人搭载2套并联机构机械臂,工控机通过算法为双臂分配采摘任务,基于四维定位信息进行路径规划与姿态解算,实现双臂协同高效作业,目前采摘速度约5秒\u002F朵,未来将不高于2秒\u002F朵。","ݽܣӵά׼Ӿλ·ʶܣ5Gֲֻͨʵʱ˽״̬򷢲ժָͬʱû˴2ײΪժеۣ˫ЭͬҵЧʡרצģ˹ɷʽȷժ̫ԭƼѧеѧԺ߽ʱʾάӾ˫ЭͬרצûڰС׼ҵ\n\n⣬ûܹ˫Эͬҵ2ײеۣػͨ㷨Ϊ˫۷ժ񣬻άλϢ·滮̬㣬ʵ˫ЭͬЧҵĿǰժٶԼ5\u002F䣬δ2\u002F䡣ڶ棬˲Ĵʽżܵ綯̣ƻ˲˵ͨ󡣳װ̫ܰ壬첻ժʱΪ﮵س磬ʡȥֻڡ䱸LEDƴΪҹҵṩ\n\nϴͳ˹ժԣժ׼ͳһ˹飻ʵҵԶңأɰҵʱ޻áµءƻܲժ˵һΪһͣ˻ƿռ䣬η겻ҵӾʶ㷨켣滮㷨Эͬ㷨һ̹ԣһ͡ñȸߵгٺͱÿĥϡͨʵҵʾ뼼Ŷռһ߷ݣ","央广网 2026-08-10","2026-08-10T00:00:00Z",79,{"impact":95,"substance":96,"depth":97,"authority":20,"freshness":98,"relevant":22,"comment":99},25,20,15,7,"黄花菜智能采摘机器人田间实操，实现从无机可用到真机下地，属农业科技重大突破，央媒报道，信息详实。",[101],{"name":91,"url":88},[28,49,103,30],"丘陵农业",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":14,"version":41,"method":42,"evidence":107},{"candidates":108,"agricultural_evidence":46},[109],{"code":33,"score":20,"supported":46,"title":110,"abstract":111,"tags":112},[49],[49],[49],[114,115],"采摘机器人 丘陵农业 黄花菜 山西","采摘机器人 丘陵农业","采摘机器人丘陵农业黄花菜山西-458",5,"2026-08-12T23:57:22.978146Z",{"id":120,"title":121,"url":122,"summary":123,"summary_zh":8,"content":124,"source_name":125,"source_url":8,"published_at":126,"category":127,"cover_url":8,"hotness":13,"is_selected":14,"score":128,"score_detail":129,"sources":131,"tags":133,"primary_topic":137,"secondary_topics":138,"classification":139,"search_phrases":162,"slug":165,"view_count":166,"doi":8,"paper":8,"created_at":167},5420,"广西印发具身智能产业创新发展五年行动计划 布局具身智能加现代农业场景","https:\u002F\u002Fwww.nanning.gov.cn\u002Fzt\u002Frdzt\u002Fyhyshj\u002Fyszc\u002Fbrphcx\u002Ft6740281.html","广西壮族自治区党委科技委员会办公室印发《具身智能产业创新发展五年行动计划（2026—2030年）》（桂科委办发〔2026〕12号），在农业领域明确要求凝练具身智能在农产品采摘、优势作物种植、养殖巡检等真实场景的技术需求，面向矿山开采、农产品采摘、海洋渔业、物流运输等场景开展特种机器人技术攻关。行动提出到2030年组织实施30项以上重点科技攻关项目、培育2家以上具身智能龙头企业、10家以上科技型中小企业、打造20个以上应用场景标杆，其中包括「具身智能+现代农业」场景。农业机器人与采摘装备由此获得明确的地方产业政策支持路径。","（十）挖掘特色应用场景需求。建立健全具身智能应用场景挖掘机制，面向企业、高校、科研院所、医疗机构等，在工业制造、教育培训、科研应用、民生服务等领域常态化征集具身智能应用场景需求，挖掘一批技术适配性强、应用价值高、示范效应好、可复制推广的具身智能应用场景。（责任单位：自治区数据局、发展改革委、教育厅、科技厅、工业和信息化厅、卫生健康委等）\n\n（十一）大力培育标杆应用场景。聚焦广西有色金属及关键金属材料、先进钢铁材料、现代绿色化工、新一代信息技术、机械及高端装备制造、新能源汽车及电池、林产加工及纸业、食品加工、生物医药及健康、绿色建材等十大支柱产业发展需求，围绕矿山无人化、高危环境巡检、材料分拣、精密装配、物料搬运、智能检测、远程运维、智能仓储等重要环节，打造“具身智能+制造业”应用场景；在优势作物种植、采摘、养殖巡检等现代农业领域开展创新应用与示范推广，打造“具身智能+现代农业”应用场景；在港口物流、能源、文旅等领域拓展具身智能应用，打造一批融合应用场景。到2030年，打造20个以上应用场景标杆。（责任单位：自治区科技厅、发展改革委、工业和信息化厅、交通运输厅、农业农村厅、文化和旅游厅、数据局等）","南宁市人民政府门户网站 2026-10-15","2026-10-15T00:00:00Z","政策",71,{"impact":17,"substance":96,"depth":18,"authority":53,"freshness":83,"relevant":22,"comment":130},"省级具身智能五年行动计划明确布局“具身智能+现代农业”场景，含2030年20个标杆等量化目标，政策条款具体，对农业机器人方向有实质参考价值。",[132],{"name":125,"url":122},[55,27,134,135,136],"具身智能","现代农业","产业规划",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":14,"version":41,"method":42,"evidence":140},{"candidates":141,"agricultural_evidence":46},[142,147,153,157],{"code":33,"score":143,"supported":46,"title":144,"abstract":145,"tags":146},4,[],[27],[27],{"code":148,"score":60,"supported":46,"title":149,"abstract":150,"tags":152},"D",[],[151],"渔业",[],{"code":52,"score":22,"supported":14,"title":154,"abstract":155,"tags":156},[],[],[55],{"code":158,"score":22,"supported":14,"title":159,"abstract":160,"tags":161},"J2",[],[],[135],[163,164],"广西 具身智能 现代农业","具身智能 农业机器人 应用场景","广西具身智能现代农业-5420",0,"2026-10-21T00:09:54.769055Z",{"id":169,"title":170,"url":171,"summary":172,"summary_zh":173,"content":8,"source_name":174,"source_url":171,"published_at":175,"category":176,"cover_url":8,"hotness":13,"is_selected":14,"score":177,"score_detail":178,"sources":181,"tags":183,"primary_topic":187,"secondary_topics":188,"classification":189,"search_phrases":205,"slug":208,"view_count":22,"doi":209,"paper":210,"created_at":231},5240,"Low-Cost Car-Like Autonomous Mobile Robot Under-Canopy Row Following, and Detection of Patterns Associated with Diseases in Plantain Crops","https:\u002F\u002Fdoi.org\u002F10.3991\u002Fijoe.v22i10.61223","Labor constraints and the need for frequent visual inspection of lower plantain (Musa paradisiaca) leaves in Colombia’s Orinoquia region motivate the development of low-cost robotic tools capable of autonomous under-canopy navigation and systematic image capture. This study reports the current stage of an ongoing research effort on a low-cost, small-scale, car-like agricultural robot for autonomous under-canopy row-following and systematic image capture in plantain fields. The platform uses a modular ROS 2 workflow, a low-cost 2D LiDAR, an inertial measurement unit, and an ESP32-based actuation layer. LiDAR data were processed through an adaptive measurement cone guided by the vehicle heading error to estimate the lateral distance to the crop row during forward row-following motion, and a fuzzy controller generated steering references. Initial field tests across five trials provided preliminary evidence of consistent under-canopy navigation under the tested conditions. In the first rowfollowing segment, the median MAE and RMSE of the lateral error were 0.0258 m and 0.0342 m, respectively; after the row-to-row maneuver, they were 0.0356 m and 0.0602 m, respectively. Additionally, an upward-facing RGB camera captured under-canopy images that were processed offline to create probability-based visual summaries of leaf-condition patterns. The results show that low-cost robotic navigation can help structure under-canopy data collection for scalable crop health monitoring in plantain plantations.","哥伦比亚奥里诺基亚地区劳动力受限，且需要对下部车前草（Musa paradisiaca）叶片进行频繁目视检查，这促使人们开发能够自主冠层下导航并系统采集图像的低成本机器人工具。本研究报道了针对一种低成本、小型、类车式农业机器人开展的在研工作的当前阶段，该机器人用于车前草田间的自主冠层下行跟随与系统图像采集。该平台采用模块化ROS 2工作流、低成本二维激光雷达、惯性测量单元以及基于ESP32的驱动层。激光雷达数据通过由车辆航向误差引导的自适应测量锥进行处理，以在前进行跟随运动中估计与作物行的横向距离，并由模糊控制器生成转向参考。在五种试验条件下的初步田间测试提供了在所测条件下冠层下导航具有一致性的初步证据。在第一个行跟随段中，横向误差的中位MAE和RMSE分别为0.0258 m和0.0342 m；在行间机动之后，分别为0.0356 m和0.0602 m。此外，一台朝上的RGB相机采集了冠层下图像，并对其进行离线处理，以生成基于概率的叶片状况模式视觉摘要。结果表明，低成本机器人导航有助于构建冠层下数据采集流程，从而支持车前草种植园中可扩展的作物健康监测。","International Journal of Online and Biomedical Engineering (iJOE)","2026-10-16T00:00:00Z","论文",70,{"impact":20,"substance":96,"depth":179,"authority":20,"freshness":21,"relevant":22,"comment":180},17,"低成本ROS 2农业机器人实现冠层下自主行跟随与叶片病害图像采集，方法新颖、田间数据初步可靠，但属细分领域阶段性成果，公共影响有限。",[182],{"name":174,"url":171},[55,27,184,185,186],"自主导航","作物病害检测","香蕉种植",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":14,"version":41,"method":42,"evidence":190},{"candidates":191,"agricultural_evidence":46},[192,197,201],{"code":33,"score":98,"supported":46,"title":193,"abstract":194,"tags":196},[],[27,195],"agricultural robot",[27],{"code":66,"score":22,"supported":14,"title":198,"abstract":199,"tags":200},[],[],[184],{"code":52,"score":22,"supported":14,"title":202,"abstract":203,"tags":204},[],[],[55],[206,207],"低成本农业机器人 大蕉 冠层导航","plantain 病害 图像检测","低成本农业机器人大蕉冠层导航-5240","10.3991\u002Fijoe.v22i10.61223",{"doi":209,"openalex_id":211,"authors":212,"venue":174,"cited_by_count":166,"oa_url":223,"card":224,"direction":228,"ingested_from":230},"W7222629670",[213,216,218,220],{"name":214,"orcid":215},"Danna Celena Montenegro","https:\u002F\u002Forcid.org\u002F0009-0003-0909-7806",{"name":217,"orcid":8},"Iván D. Duarte",{"name":219,"orcid":8},"Andres Leonardo Jutinico",{"name":221,"orcid":222},"Henry Borrero Guerrero","https:\u002F\u002Forcid.org\u002F0000-0003-4243-4205","https:\u002F\u002Fonline-journals.org\u002Findex.php\u002Fi-joe\u002Farticle\u002Fdownload\u002F61223\u002F17460",{"tldr":225,"method":226,"finding":227,"direction":228,"opportunity":229},"开发低成本类车机器人实现车前草冠层下自主行跟随与图像采集。","ROS 2、2D LiDAR、IMU、ESP32及模糊控制器，离线处理RGB图像","横向误差中位数MAE约0.026-0.036米，验证了低成本导航可行性。","智慧农业 \u002F 农业物联网","可研究多行自主切换、病害图像在线识别及复杂冠层下鲁棒导航。","openalex","2026-10-18T23:30:09.565705Z",{"id":233,"title":234,"url":235,"summary":236,"summary_zh":237,"content":8,"source_name":238,"source_url":235,"published_at":239,"category":176,"cover_url":8,"hotness":13,"is_selected":14,"score":240,"score_detail":241,"sources":244,"tags":246,"primary_topic":250,"secondary_topics":251,"classification":252,"search_phrases":263,"slug":266,"view_count":22,"doi":267,"paper":268,"created_at":301},4991,"Direct‐Printed Textile Circuits for Smart Gloves With Enhanced Integration","https:\u002F\u002Fdoi.org\u002F10.1002\u002Fadem.71290","Integrating deformable sensors, conductive routing, embedded electronics, and local data processing on a textile carrier remains challenging for wearable gesture interfaces. Here, a direct‐printed textile circuit smart glove was constructed using a hybrid textile–electronic architecture. Low‐resistance carbon paste and Ag paste were sequentially screen‐printed to form the strain‐sensitive layer, electrodes, interconnects, and component pads. Packaged modules were attached with silver‐filled epoxy electrically conductive adhesive and protected by localized silicone‐rubber encapsulation. The sensor produced a linear response over 2.5%–15% strain ( R 2 = 0.9995), with response and recovery times of approximately 200 and 100 ms, and stable electrical output during a 10 000s test corresponding to about 4000 cycles at 0.4 Hz. An ESP32‐based threshold classifier processed five finger channels locally and recognized eight static gestures with an average accuracy of 95.2% over 480 trials. The encoded gestures were then used to command a uHand 2.0 bionic hand and an agricultural robot. These results demonstrate the system‐level feasibility of the hybrid textile–electronic architecture for integrating textile sensing, on‐device gesture recognition, wireless communication, and robotic command execution.","将可变形传感器、导电布线、嵌入式电子器件和本地数据处理集成到纺织品载体上，对于可穿戴手势接口而言仍具挑战性。本文采用混合纺织-电子架构构建了一种直写印刷纺织电路智能手套。通过依次丝网印刷低阻碳浆和银浆，形成应变敏感层、电极、互连线和元件焊盘。封装模块采用银填充环氧导电胶粘接，并通过局部硅橡胶封装进行保护。该传感器在2.5%–15%应变范围内呈线性响应（R² = 0.9995），响应时间和恢复时间分别约为200 ms和100 ms，在10 000 s测试（对应0.4 Hz下约4000次循环）中电输出保持稳定。基于ESP32的阈值分类器在本地处理五个手指通道，在480次试验中以平均95.2%的准确率识别八种静态手势。随后，编码手势被用于控制uHand 2.0仿生手和一台农业机器人。这些结果证明了混合纺织-电子架构在集成纺织传感、设备端手势识别、无线通信和机器人指令执行方面的系统级可行性。","Advanced Engineering Materials","2026-10-14T00:00:00Z",81,{"impact":17,"substance":242,"depth":17,"authority":19,"freshness":21,"relevant":22,"comment":243},22,"直印纺织电路智能手套实现本地手势识别并驱动农业机器人，系统级验证扎实，对农业人机交互有参考价值。",[245],{"name":238,"url":235},[55,27,247,248,249],"可穿戴设备","人机交互","柔性传感",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":14,"version":41,"method":42,"evidence":253},{"candidates":254,"agricultural_evidence":46},[255,259],{"code":33,"score":98,"supported":46,"title":256,"abstract":257,"tags":258},[],[27,195],[27],{"code":52,"score":22,"supported":14,"title":260,"abstract":261,"tags":262},[],[],[55],[264,265],"直印纺织电路 智能手套","ESP32 手势识别 农业机器人","直印纺织电路智能手套-4991","10.1002\u002Fadem.71290",{"doi":267,"openalex_id":269,"authors":270,"venue":238,"cited_by_count":166,"oa_url":8,"card":296,"direction":228,"ingested_from":230},"W7221824460",[271,273,275,277,279,281,283,285,288,290,293],{"name":272,"orcid":8},"Hao Wu",{"name":274,"orcid":8},"Huimin Ren",{"name":276,"orcid":8},"Shubei Zhi",{"name":278,"orcid":8},"Xutao Huang",{"name":280,"orcid":8},"Junxian Guo",{"name":282,"orcid":8},"Siyu Li",{"name":284,"orcid":8},"Lingxiao Cao",{"name":286,"orcid":287},"Zhonghao Wang","https:\u002F\u002Forcid.org\u002F0009-0004-7227-3929",{"name":289,"orcid":8},"Yunlong Ni",{"name":291,"orcid":292},"Zhi‐Zhu He","https:\u002F\u002Forcid.org\u002F0000-0001-8861-9964",{"name":294,"orcid":295},"Zhen Li","https:\u002F\u002Forcid.org\u002F0000-0001-6010-0298",{"tldr":297,"method":298,"finding":299,"direction":228,"opportunity":300},"开发直接印刷纺织电路智能手套，集成传感、本地手势识别与机器人控制。","丝网印刷碳\u002F银浆料制备柔性电路，ESP32本地阈值分类，控制仿生手与农业机器人。","传感器线性度R²=0.9995，8种手势识别平均准确率95.2%，可稳定控制机器人。","可探索将智能手套用于农业机器人遥操作、采摘辅助或农户动作数据采集与技能数字化。","2026-10-15T23:30:09.135126Z",{"id":303,"title":304,"url":305,"summary":306,"summary_zh":8,"content":8,"source_name":307,"source_url":8,"published_at":308,"category":127,"cover_url":8,"hotness":13,"is_selected":14,"score":309,"score_detail":310,"sources":314,"tags":316,"primary_topic":320,"secondary_topics":321,"classification":322,"search_phrases":354,"slug":357,"view_count":166,"doi":8,"paper":8,"created_at":358},4837,"山东出台数字强省建设'十五五'规划 建设特色农业'大脑'支持30个智慧农业应用场景","https:\u002F\u002Fnew.qq.com\u002Frain\u002Fa\u002F20261012A08ZIW00","山东发布数字强省建设'十五五'规划,在农业数智化方面,实施'人工智能+农业'行动,开展农业传感器与专用芯片、模型算法等研发攻关,大力发展智能农机与农业机器人,支持'无人农场'建设。建设特色农业'大脑',省级每年支持建设30个智慧农业应用场景,支持德州、聊城'吨半粮'等引领区数智化建设。建好用好'齐鲁农云''齐鲁农超''好粮有网'等平台,打造农业农村'数字大脑',建设80个数字农业发展县。","腾讯新闻 2026 年 10 月 12 日","2026-10-12T00:00:00Z",77,{"impact":242,"substance":311,"depth":17,"authority":83,"freshness":312,"relevant":22,"comment":313},23,8,"省级数字强省规划含农业数智化具体条款与量化目标，信息增量足，值得进入每日精选。",[315],{"name":307,"url":305},[317,55,318,319,27],"数字乡村","无人农场","农业人工智能",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":14,"version":41,"method":42,"evidence":323},{"candidates":324,"agricultural_evidence":46},[325,330,334,338,344,349],{"code":52,"score":97,"supported":46,"title":326,"abstract":327,"tags":329},[55],[55,328],"数字农业",[55],{"code":33,"score":312,"supported":46,"title":331,"abstract":332,"tags":333},[],[27,318],[27,318],{"code":66,"score":60,"supported":46,"title":335,"abstract":336,"tags":337},[],[69],[],{"code":339,"score":60,"supported":46,"title":340,"abstract":341,"tags":343},"I5",[],[342],"农业传感",[],{"code":345,"score":22,"supported":14,"title":346,"abstract":347,"tags":348},"I2",[],[],[319],{"code":350,"score":22,"supported":14,"title":351,"abstract":352,"tags":353},"I6",[],[],[317],[355,356],"山东 数字强省 十五五规划","齐鲁农云 智慧农业应用场景","山东数字强省十五五规划-4837","2026-10-14T00:04:01.888905Z",{"id":360,"title":361,"url":362,"summary":363,"summary_zh":8,"content":8,"source_name":364,"source_url":8,"published_at":365,"category":176,"cover_url":8,"hotness":13,"is_selected":14,"score":366,"score_detail":367,"sources":369,"tags":371,"primary_topic":374,"secondary_topics":375,"classification":376,"search_phrases":399,"slug":402,"view_count":166,"doi":8,"paper":403,"created_at":411},4734,"面向农业机器人作物行分割的边缘可部署轻量感知网络","https:\u002F\u002Farxiv.org\u002Fabs\u002F2610.11764","提出仅1.31万参数、逐层渐进学习的作物行分割网络,推理能耗25.1毫焦,较主流网络参数量显著降低且保持检测精度。适配资源受限田间机器人部署,定位低成本农机边缘智能新路径。未经实地验证未经同行评议","arXiv 2026-10-08 [预印本]","2026-10-08T00:00:00Z",66,{"impact":19,"substance":96,"depth":179,"authority":312,"freshness":98,"relevant":22,"comment":368},"预印本提出超轻量作物行分割网络，参数与能耗指标亮眼，但未经实地验证与同行评议，属细分技术进展，可作精选备选。",[370],{"name":364,"url":362},[55,319,27,372,373],"边缘计算","作物行识别",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":14,"version":41,"method":42,"evidence":377},{"candidates":378,"agricultural_evidence":46},[379,383,387,391,395],{"code":33,"score":21,"supported":46,"title":380,"abstract":381,"tags":382},[27],[],[27],{"code":66,"score":60,"supported":46,"title":384,"abstract":385,"tags":386},[],[69],[],{"code":52,"score":22,"supported":14,"title":388,"abstract":389,"tags":390},[],[],[55],{"code":345,"score":22,"supported":14,"title":392,"abstract":393,"tags":394},[],[],[319],{"code":339,"score":22,"supported":14,"title":396,"abstract":397,"tags":398},[],[],[372],[400,401],"作物行分割 轻量网络 农业机器人","边缘部署 作物行 田间机器人","作物行分割轻量网络农业机器人-4734",{"doi":8,"openalex_id":8,"authors":404,"venue":8,"cited_by_count":166,"oa_url":8,"card":405,"direction":228,"ingested_from":410},[],{"tldr":406,"method":407,"finding":408,"direction":228,"opportunity":409},"提出仅1.31万参数的轻量作物行分割网络，适配田间机器人边缘部署。","逐层渐进学习，参数量1.31万，推理能耗25.1毫焦。","参数量显著降低且保持检测精度，定位低成本农机边缘智能路径。","该网络未经实地验证，可开展田间试验并探索多作物、多光照条件下的泛化能力。","agent","2026-10-12T00:11:14.925915Z"]