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| 1 | Development and evaluation of a general-purpose electric off-road robot based on agricultural navigation显示文摘The aim of this study was to develop a general-purpose electric off-road robot vehicle by using automatic control technologies.The vehicle prototype used in this study was a commercially-purchased electricity utility vehicle that was designed originally for manual operations.A manipulating unit,an automatic steering system and a speed control system were developed and integrated into a CAN-bus network for operating on functions(forward,reverse,park or stop),realizing desired steering angles and maintaining a constant speed,respectively,in the mode of automation.An autonomous navigation system based on RTK-GPS and IMU was used to evaluate the performance of the newly developed off-road robot.Field tests showed that the maximum error in speed control was 0.29 m/s and 0.22 m/s for speed tests and autonomous runs,respectively.The lateral offset was less than 10 cm in terms of straight paths,indicating that the automatic steering control system was of good performance. | Yin Xiang Noboru Noguchi | 2014 | International Journal of Agricultural and Biological Engineering2014，7，5： | 6 |
| 2 | Development of autonomous navigation system for rice transplanter显示文摘Rice transplanting requires the operator to manipulate the rice transplanter in straight trajectories.Various markers are proposed to help experienced drivers in keeping straightforward and parallel to the previous path,which are extremely boring in terms of large-scale fields.The objective of this research was to develop an autonomous navigation system that automatically guided a rice transplanter working along predetermined paths in the field.The rice transplanter used in this research was commercially available and originally manually-operated.An automatic manipulating system was developed instead of manual functions including steering,stop,going forward and reverse.A sensor fusion algorithm was adopted to integrate measurements of the Real-Time Kinematic Global Navigation Satellite System(RTK-GNSS)and Inertial Measurement Unit(IMU),and calculate the absolute moving direction under the UTM coordinate system.A headland turning control method was proposed to ensure a robust turning process considering that the rice transplanter featured a small turning radius and a relatively large slip rate at extreme steering angles.Experiments were designed and conducted to verify the performance of the newly developed autonomous navigation system.Results showed that both lateral and heading errors were less than 8 cm and 3 degrees,respectively,in terms of following straight paths.And headland turns were robustly executed according to the required pattern. | Xiang Yin Juan Du Noboru Noguchi Tengxiang Yang Chengqian Jin | 2018 | International Journal of Agricultural and Biological Engineering2018，11，6： | 6 |
| 3 | Development of uncut crop edge detection system based on laser rangefinder for combine harvesters显示文摘The objective of this research was to develop an uncut crop edge detection system for a combine harvester.A laser rangefinder(LF)was selected as a primary sensor,combined with a pan-tilt unit(PTU)and an inertial measurement unit(IMU).Three-dimensional field information can be obtained when the PTU rotates the laser rangefinder in the vertical plane.A field profile was modeled by analyzing range data.Otsu’s method was used to detect the crop edge position on each scanning profile,and the least squares method was applied to fit the uncut crop edge.Fundamental performance of the system was first evaluated under laboratory conditions.Then,validation experiments were conducted under both static and dynamic conditions in a wheat field during harvesting season.To verify the error of the detection system,the real position of the edge was measured by GPS for accuracy evaluation.The results showed an average lateral error of±12 cm,with a Root-Mean-Square Error(RMSE)of 3.01 cm for the static test,and an average lateral error of±25 cm,with an RMSE of 10.15 cm for the dynamic test.The proposed laser rangefinder-based uncut crop edge detection system exhibited a satisfactory performance for edge detection under different conditions in the field,and can provide reliable information for further study. | Zhao Teng Noboru Noguchi Yang Liangliang Kazunobu Ishii Chen Jun | 2016 | International Journal of Agricultural and Biological Engineering2016，9，2： | 5 |
| 4 | Development and evaluation of a low-cost precision seeding control system for a corn drill显示文摘Precision seeding requires that the corn drill drop seeds into the soil by a specific in-row spacing while its travelling speed fluctuates due to unevenness of the field ground.This paper presents a low-cost precision seeding control system for a conventional corn drill with mechanical metering devices of finger-pickup type.A median filtering method was implemented in the control system to process measurements from a rotary encoder in order to acquire stable values of the corn drill travelling speed.The metering unit was driven by an electric motor controlled by the metering ECU according to the actual travelling speed and the desired in-row spacing in real-time.A user interface was programmed to communicate with ECUs for configuring parameters and displaying operating information during working.The newly-developed precision seeding control system was first calibrated in terms of speed measurement and control for two ECUs.Experiments were conducted on a seeding test platform in the laboratory for evaluating its accuracy in dropping seeds by giving different in-row spacing under different travelling speeds of the conveyor sticky belt.Results showed that the average spacing error was less than 2 cm and the maximum RMS error was 0.78 cm for all spacing values including 25 cm,30 cm and 35 cm under the travelling speed of 1.0-8.0 km/h.These indicated that the low-cost precision seeding control system worked in a both accurate and stable way. | Xiang Yin Noboru Noguchi Tengxiang Yang Chengqian Jin | 2018 | International Journal of Agricultural and Biological Engineering2018，11，5： | 3 |
| 5 | 精细农业机械化作物生产计算机集成技术(英文)显示文摘介绍了一项适用于精细农业机械化的新技术计算机集成作物生产技术(CCP)。该技术融合信息采集、网络通讯、数据处理、过程决策、自动执行等功能,能有效地完成作物生产的精确机械化作业。计算机集成作物生产技术的3个主要功能是先根据需要实时采集传感数据,然后根据传感信息构建合理的行动决策,最后将传递上述决策并付诸实施。为了说明CCP的工作原理和结构设计,介绍了由伊利诺依大学机械电子系统实验室设计开发的CCP技术系统的关键功能。研究结果表明,在车辆自动导航,主从机械控制,在线式变量作业等利用农业机械实施田间作物生产作业的领域,有必要在农业机械上集成CCP技术,使机械自动地完成各项最优化项目作业。最后,根据以往工作中的经验,简要讨论了目前CPP技术发展所面临的问题和挑战。 | 何勇 张勤 Alan Hansen Noboru Noguchi Beom-soo Shin | 2006 | 农业工程学报2006，22，11： | 3 |
| 6 | Agricultural automatic guidance research in North America显示文摘 | John F. Reid Qin Zhang Noboru Noguchi Monte Dickson | 2000 | Computers and Electronics in Agriculture2000，，1： | 3 |
| 7 | Adaptive turning control for an agricultural robot tractor显示文摘An adaptive turning algorithm for a four-wheel robot tractor in the headland is presented in this paper.The navigation sensors consisted of an inertial measurement unit and a real-time kinematic global positioning system(GPS).An objective function based on weights was used to create the navigation path,connecting by continuous primitives.The asymmetric steering mechanism was then taken into consideration with a vehicle model.To follow the path accurately,the slide movement of the robot and the steering rate were taken into account by estimating the turning radius in real time.In addition,the vehicle model was tuned based on the results of each turn.Therefore,the turning control algorithm was optimized on the basis of the specific conditions in the field.Field experiments showed that the robot tractor approached the next path with an average lateral deviation of 3.9 cm at a speed of 1.2 m/s during a turn.Compared to a conventional turning scheme,the time consumption and turning trajectory were decreased by 17%and 21%,respectively. | Hao Wang Noboru Noguchi | 2018 | International Journal of Agricultural and Biological Engineering2018，11，6： | 3 |
| 8 | Multi-temporal monitoring of wheat growth by using images from satellite and unmanned aerial vehicle显示文摘Recently near-ground remote sensing using unmanned aerial vehicles(UAV)witnessed wide applications in obtaining field information.In this research,four Rapideye satellite images and eight RGB images acquired from UAV were used from early June to the end of July,2015 covering two experimental winter wheat fields,in order to monitor wheat canopy growth status and analyze the correlation among satellite images based normalized difference vegetation index(NDVI)with UAV’s RGB images based visible-band difference vegetation index(VDVI)and ground variables of the sampled grain protein contents.Firstly,through image interpretation of UAV’s multi-temporal RGB images with fine spatial resolution,the wheat canopy color changes could be intuitively and clearly monitored.Subsequently,by monitoring the changes of satellite images based NDVI as well as VDVI values and UAV’s RGB images based VDVI values,the conclusions were made that these three vegetation indices demonstrated the same and synchronized trend of increasing at the early stage of wheat growth season,reaching up to peak values at the same timing,and starting to decrease since then.The results of the correlation analysis between NDVI of satellite images and sampled grain protein contents show that NDVI has good predicative capability for mapping grain protein content before ripening growth stage around June7,2015,while the reliability of using satellite image based NDVI to predict grain protein contents becomes worse as ripening stage approaches.The regression analysis between UAV’s RGB image based VDVI and satellite image based VDVI as well as NDVI showed good coefficients of determination.It is concluded that it is feasible and practical to temporally complement satellite remote sensing by using UAV’s RGB images based vegetation indices to monitor wheat growth status and to map within-field spatial variations of grain protein contents for small scale farmlands. | Du Mengmeng Noguchi Noboru Itoh Atsushi Shibuya Yukinori | 2017 | International Journal of Agricultural and Biological Engineering2017，10，5： | 3 |
| 9 | Improved inclination correction method applied to the guidance system of agricultural vehicles显示文摘This research introduces a new inclination correction method with increased accuracy applied to the guidance system of an agricultural vehicle.The method considers the geometry of a robot tractor and uses an Inertial Measurement Unit(IMU)to correct the lateral error of the RTK-GPS antenna measurements raised by the tractor's inclinations.A parameters optimization experiment and an automatic guidance experiment under real working conditions were used to compare the accuracy of a traditional correction method with the new correction method,by calculating the RMSE of the lateral error and the error reduction percentage.An additional tuned correction method was found by using a simple analytical method to find the optimal variables that reduced the lateral error to a minimum.The results indicate that the new correction method and the tuned correction method display a significant error reduction percentage compared to the traditional correction method.The methods could correct the GPS lateral error caused by the roll inclinations in real-time.The resulting lateral deviation caused by the tractor's inclinations could be reduced up to 23%for typical travelling speeds. | Ricardo Ospina Noboru Noguchi | 2020 | International Journal of Agricultural and Biological Engineering2020，13，6： | 2 |
| 10 | 日本机器人耕作体系与遥感技术应用显示文摘日本稻米自给自足率国家政策目标,到2021年时将比现在增加50%。由于日本社会老龄化严重,农民数量减少,越来越多的稻田被荒废,让人感到十分可惜。同时,日本由于耕地比较分散, | Noboru Noguchi | 2010 | 农机科技推广2010，，12： | 2 |
| 11 | Agricultural automatic guidance research in North America显示文摘 | John FReid Qin Zhang Noboru Noguchi | 2000 | Computers and Electronics in Agriculture2000，25，： | 1 |
| 12 | The development of the autonomous tractor with steering controller applied by optimal control 显示文摘 | Michio Kise Noboru Noguchi Kazunobu Ishii | 2002 | ASAE Publication Number 701P05022002，，： | 1 |
| 13 | Studies on self-learning autonomous vehicles (Part 1): Following control using neuro-controller显示文摘 | Kazunobu ISHII Hideo TERAO Noboru NOGUCHI | 1994 | Journal of the Japanese Society of Agricultural Machinery1994，56，4： | 1 |
| 14 | Development of robot tractor based on RTK-GPS and gyroscope 显示文摘 | Noboru Noguchi John F Reid Qin Zhang | 2001 | ASAE Paper Number: 01 - 11952001，，： | 1 |
| 15 | Optimal control of agricultural vehicles by neural network (Part 2): Optimal schedule of working route by genetic algorithms 显示文摘 | Noboru Noguchi Kazunobu Ishii Hideo Terao | 1994 | Journal of the Japanese Society of Agricultural Machinery1994，56，2： | 1 |
| 16 | Agricultural automatic guidance research in North America 显示文摘 | John F Reid Qin Zhang Noboru Noguchi | 2000 | Computers and Electronics in Agriculture2000，25，： | 1 |
| 17 | Design and performance of a robotic arm for farm use显示文摘Smart technology which is the backbone of high-efficiency production opens a new horizon in sustainable agriculture.Nowadays,harvesting the heavy-weight crops is considered an arduous job,specifically in Japan which has faced a serious labor shortage in agricultural fields.In this study,a development procedure and evaluation of a 4-degrees-of-freedom articulated robotic arm is presented,and it provides an appropriate infrastructure to develop a smart harvesting robotic system for heavy-weight crops such as pumpkin,watermelon,melon,and cabbage.This robotic arm designed as an actuating unit of a robot tractor for the agricultural outdoor environment.In this regard,different degree of freedom was evaluated under consideration of economic and technical indexes to find an optimized mechanism.The controlling algorithm of the system was developed by consideration of kinematic and dynamic aspects of the real-world condition.A special harvesting methodology was developed based on optimum harvesting conditions.A controlling unit was developed by using PLC system.Experimental performance,accuracy,payload per weight,and repeatability of the system were measured.The payload per weight,overall average accuracy,and overall average repeatability of the robot were 0.21,1.85 mm,and±0.51 mm,respectively.The results indicated that the developed system had a front access,harvesting length,and workspace volume of 2.024 m,1.36 m,and 8.27 m^(3),respectively.One of the significant advantages of the proposed robotic arm is its capability to use in different industries with minimum modifications. | Ali Roshanianfard Noboru Noguchi Tatsuki Kamata | 2019 | International Journal of Agricultural and Biological Engineering2019，12，1： | 1 |
| 18 | Agricultural automatic guidance research in North America显示文摘 | John F Reid Qin Zhang Noboru Noguchi | 2000 | Computers and Electronics in Agriculture2000，25，12： | 1 |
| 19 | A new algorithm for ABS to compensate for road-disturbance显示文摘 | Masso Watanabe Noboru Noguchi | | SAE Paper0，，： | 1 |
| 20 | Development of phenotyping system using low altitude UAV imagery and deep learning显示文摘In this study,a lightweight phenotyping system that combined the advantages of both deep learning-based panicle detection and the photogrammetry based on light consumer-level UAVs was proposed.A two-year experiment was conducted to perform data collection and accuracy validation.A deep learning model,named Mask Region-based Convolutional Neural Network(Mask R-CNN),was trained to detect panicles in complex scenes of paddy fields.A total of 13857 images were fed into Mask R-CNN,with 80%used for training and 20%used for validation.Scores,precision,recall,Average Precision(AP),and F1-score of the Mask R-CNN,were 82.46%,80.60%,79.46%,and 79.66%,respectively.A complete workflow was proposed to preprocess flight trajectories and remove repeated detection and noises.Eventually,the evident changed in rice growth during the heading stage was visualized with geographic distributions,and the total number of panicles was predicted before harvest.The average error of the predicted amounts of panicles was 33.98%.Experimental results showed the feasibility of using the developed system as the high-throughput phenotyping approach. | Suxing Lyu Noboru Noguchi Ricardo Ospina Yuji Kishima | 2021 | International Journal of Agricultural and Biological Engineering2021，14，1： | 1 |
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