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蒙自 测产","云南农科院 水稻 全程机械化","粒两优8022蒙自测产-3649","2026-09-28T00:03:01.223003Z",{"id":353,"title":354,"url":355,"summary":356,"summary_zh":8,"content":357,"source_name":358,"source_url":8,"published_at":359,"category":11,"cover_url":8,"hotness":99,"is_selected":13,"score":360,"score_detail":361,"sources":363,"tags":365,"primary_topic":370,"secondary_topics":371,"classification":373,"search_phrases":405,"slug":408,"view_count":85,"doi":8,"paper":8,"created_at":409},955,"重庆梁平：水稻收割实现「无人化」 「渝东粮仓」智能农机成新帮手","https:\u002F\u002Fwww.farmer.com.cn\u002F2026\u002F08\u002F25\u002F991026753.html","秋收时节，重庆市梁平区运用无人驾驶收割机收割水稻。农技人员通过北斗定位和5G技术，设定参数自主规划最优路线，无人驾驶收割机便可在农田中精准完成水稻收割，既降低劳动强度，让收割更加精准、更加智能，又提高了生产效率。近年来在「渝东粮仓」梁平区，无人旋耕机、无人插秧机、无人植保机、无人驾驶收割机等新型智能化设备纷纷亮相，成为农业生产的好帮手，提高了农业现代化技术装备水平和农业综合生产能力，助力乡村全面振兴。","秋收时节，重庆市梁平区运用无人驾驶收割机收割水稻。农技人员通过北斗定位和5G技术，设定参数自主规划最优路线，无人驾驶收割机便可在农田中精准完成水稻收割，既降低劳动强度，让收割更加精准、更加智能，又提高了生产效率。\n\n近年来，在“渝东粮仓”重庆市梁平区，无人旋耕机、无人插秧机、无人植保机、无人驾驶收割机等新型智能化设备纷纷亮相田间地头，成为农业生产的好帮手，提高了农业机械化水平和农业综合生产能力，助力乡村全面振兴。","中国农网 2026-08-25","2026-08-25T07:36:11Z",53,{"impact":19,"substance":19,"depth":99,"authority":99,"freshness":104,"relevant":21,"comment":362},"地方农业智能化应用报道，有具体案例但缺乏深度分析，信源为行业媒体，时效性好。",[364],{"name":358,"url":355},[189,366,367,217,368,369],"北斗","重庆梁平","5G","渝东粮仓",{"code":35,"slug":36,"name":30,"path":37,"parent_code":38},[372],{"code":41,"slug":42,"name":43,"path":44,"parent_code":45},{"status":47,"locked":13,"version":48,"method":49,"evidence":374},{"candidates":375,"agricultural_evidence":53},[376,380,384,388,392,396,400],{"code":41,"score":19,"supported":53,"title":377,"abstract":378,"tags":379},[208],[206],[189],{"code":35,"score":269,"supported":53,"title":381,"abstract":382,"tags":383},[30],[30],[],{"code":323,"score":71,"supported":53,"title":385,"abstract":386,"tags":387},[],[326],[],{"code":232,"score":71,"supported":53,"title":389,"abstract":390,"tags":391},[],[191],[],{"code":226,"score":71,"supported":53,"title":393,"abstract":394,"tags":395},[],[229],[],{"code":197,"score":21,"supported":13,"title":397,"abstract":398,"tags":399},[],[],[217],{"code":401,"score":21,"supported":13,"title":402,"abstract":403,"tags":404},"I5",[],[],[368],[406,407],"无人收割机 智能农机 渝东粮仓 重庆梁平","无人收割机 智能农机","无人收割机智能农机渝东粮仓重庆梁平-955","2026-08-26T00:09:29.784138Z",{"id":411,"title":412,"url":413,"summary":414,"summary_zh":8,"content":415,"source_name":416,"source_url":8,"published_at":417,"category":98,"cover_url":8,"hotness":99,"is_selected":13,"score":182,"score_detail":418,"sources":420,"tags":422,"primary_topic":427,"secondary_topics":428,"classification":430,"search_phrases":447,"slug":450,"view_count":221,"doi":8,"paper":8,"created_at":451},796,"[预印本]自主农业拖拉机:面向精准稻作的集成杂草检测与LiDAR导航系统(原标题:Autonomous Agricultural Tractor: Integrated Weed Detection and LiDAR Navigation for Precision Paddy Farming)","https:\u002F\u002Farxiv.org\u002Fabs\u002F2608.19004","稻田定点杂草管理相比传统广域喷药可大幅减少除草剂用量,但现场部署受三大挑战制约:冠层下GNSS退化的稳健作物行导航、稻与形态多样化杂草的实时视觉区分、将稻误识为杂草的不可逆错误代价。本研究提出AgriNav,围绕四个ROS耦合模块构建集成自主拖拉机系统:用于稻检测的WeedDet PyTorch重实现、并行轻量级168万参数CNN-FPN变体(带非对称类加权)、通过硬编码置信门否决保护稻类的逆逻辑判别模块,以及融合GNSS\u002FIMU\u002F轮式里程计的6状态恒定速度转向率扩展卡尔曼滤波。主要系统级贡献是LiDAR-相机融合桥,利用导航LiDAR做ROI约束、世界坐标投影、地面平面滤波和双向置信融合,无额外硬件成本。","[View PDF](https:\u002F\u002Farxiv.org\u002Fpdf\u002F2608.19004)[HTML (experimental)](https:\u002F\u002Farxiv.org\u002Fhtml\u002F2608.19004v1)\n\n> Abstract:Site-specific weed management in paddy farming offers substantial reductions in herbicide use over conventional broadcast spraying, but field deployment has been limited by three persistent challenges: robust crop-row navigation under canopy where GNSS degrades, real-time visual discrimination between rice and morphologically diverse weeds, and the asymmetric cost of misclassifying rice as weed, which is irreversible. \n> \n> This paper presents AgriNav, an integrated autonomous tractor system built around four ROS-coupled modules: a custom PyTorch reimplementation of WeedDet for rice detection, a parallel lightweight 1.68M-parameter CNN-FPN variant with asymmetric class weighting, an inverted-logic discrimination module that protects the rice class through a hardcoded confidence-gate veto, and a 6-state constant-velocity-turn-rate Extended Kalman Filter fusing GNSS, IMU, and wheel odometry with three-level outage bridging. Our primary system-level contribution is a four-mechanism LiDAR-camera fusion bridge that uses the navigation LiDAR for region-of-interest constraint, world-coordinate projection, ground-plane filtering, and bidirectional confidence fusion at zero additional hardware cost. \n> \n> Simulation experiments demonstrate continuous position tracking through a 20-second GNSS outage, crop row detection confidence above 0.9 throughout operation, and rice-detection confidences from 0.32 to 0.95 across paddy, aerial, and post-flood imagery. The LiDAR ROI constraint reduces detection inference region by an estimated 30 to 50 percent.\n\nSubjects:Robotics (cs.RO); Computer Vision and Pattern Recognition (cs.CV)\nCite as:[arXiv:2608.19004](https:\u002F\u002Farxiv.org\u002Fabs\u002F2608.19004) [cs.RO]\n(or [arXiv:2608.19004v1](https:\u002F\u002Farxiv.org\u002Fabs\u002F2608.19004v1) [cs.RO] for this version)\n[https:\u002F\u002Fdoi.org\u002F10.48550\u002FarXiv.2608.19004](https:\u002F\u002Fdoi.org\u002F10.48550\u002FarXiv.2608.19004)\n\narXiv-issued DOI via DataCite (pending registration)\n\n## Submission history\n\nFrom: Sudip Dhakal [[view email](https:\u002F\u002Farxiv.org\u002Fshow-email\u002Ff6fe364c\u002F2608.19004)] \n\n**[v1]** Wed, 19 Aug 2026 15:04:22 UTC (1,887 KB)","arXiv:2608.19004 2026-08-19 [预印本]","2026-08-19T07:04:00Z",{"impact":19,"substance":16,"depth":102,"authority":99,"freshness":215,"relevant":21,"comment":419},"面向精准稻作的自主拖拉机系统，集成杂草检测与LiDAR导航，技术细节丰富，但属预印本且应用场景特定，影响范围有限。",[421],{"name":416,"url":413},[423,424,425,426,123],"预印本","自主拖拉机","LiDAR导航","杂草检测",{"code":35,"slug":36,"name":30,"path":37,"parent_code":38},[429],{"code":41,"slug":42,"name":43,"path":44,"parent_code":45},{"status":47,"locked":13,"version":48,"method":49,"evidence":431},{"candidates":432,"agricultural_evidence":53},[433,437,442],{"code":35,"score":269,"supported":53,"title":434,"abstract":435,"tags":436},[121],[123],[],{"code":41,"score":215,"supported":53,"title":438,"abstract":440,"tags":441},[439],"tractor",[],[],{"code":323,"score":71,"supported":53,"title":443,"abstract":444,"tags":446},[],[445],"除草",[],[448,449],"自主拖拉机 杂草检测 预印本 LiDAR导航","自主拖拉机 杂草检测","自主拖拉机杂草检测预印本LiDAR导航-796","2026-08-21T00:05:57.744668Z"]