Development of the electric automatic steering system for agricultural vehicles

Automatic guidance of agricultural vehicles requires automatic execution of operation commands received from the navigation controller by using electronically controlled mechanisms for wheel steering,speed changing and work implementing.Automatic steering contributes as a prerequisite technique in automatic and semi-automatic agricultural navigation.This research aimed to develop an electric automatic steering system that was compact in its structure and integrated into original steering mechanism in a simply and convenient way for aftermarket modification.A brushless motor and reducer assembly was utilized to provide an adequate steering torque instead of manual maneuver.A rapid assembling approach was proposed by passing the steering shaft through the hollow output shaft.A digital proportional-integral-differential(PID)algorithm was implemented to calculate the rotation speeds and directions by comparing the desired angle and the actual angle,which was implemented in a printed circuit board with a microcontroller unit(MCU)and interface chips.An unmanned wheeled tractor was applied as test platform to integrate the newly developed electric automatic steering system.Tests were conducted to evaluate its performance in terms of stability and responsiveness.An autonomous navigation system guided the tractor along target paths in the field by sending steering commands to the electric automatic steering system.The results show that the steering angle error was less than 0.81°when desired steering angle was less than 10°.The lateral error difference was no more than 4.76 cm when repeating following the same target path,which indicated that the electric automatic steering system responded accurately and robustly to steering commands.

Autonomous trajectory tracking control method for an agricultural robotic vehicle

To address the nonlinearities and external disturbances in unstructured and complex agricultural environments,this paper investigates an autonomous trajectory tracking control method for agricultural ground vehicles.Firstly,this paper presents the design and implementation of a lightweight,modular two-wheeled differential drive vehicle equipped with two drive wheels and two caster wheels.The vehicle comprises drive wheel modules,passive wheel modules,battery modules,a vehicle frame,a sensor system,and a control system.Secondly,a novel robust trajectory tracking method was proposed,utilizing an improved pure pursuit algorithm.Additionally,an Online Particle Swarm Optimization Continuously Tuned PID(OPSO-CTPID)controller was introduced to dynamically search for optimal control gains for the PID controller.Simulation results demonstrate the superiority of the improved pure pursuit algorithm and the OPSO-CTPID control strategy.To validate the performance,the vehicle was integrated with a seeding and fertilizing machine to realize autonomous wheat seeding in an agricultural environment.Experimental outcomes reveal that the vehicle of this study completed a seeding operation exceeding 1 km in distance.The proposed method can robustly and smoothly track the desired trajectory with an accuracy of less than 10 cm for the root mean square error(RMSE)of the curve and straight lines,given a suitable set of parameters,meeting the requirements of agricultural applications.The findings of this study hold significant reference value for subsequent research on trajectory tracking algorithms for ground-based agricultural robots.

Design and Development of a Forest Nursery, for the Enhancement of Multi-Functional Agriculture and for a Didactical Purpose

The experimental idea of the present project was elaborated in order to create a structure where different categories and institutions could collaborate, with the common aim to develop a sustainable and profitable agriculture in mountain and marginal areas. The target was the recovering of an abandoned agricultural site, throughout its re-organisation, re-qualification and auto-sustainability, involving local citizens. This approach was based on three further broad functions such as environmental, economic and social purposes. This cooperation, that allows the capitalization of local knowledge and the forging of relationships between local and external sources of expertise, information and advice, is fundamental to the future of existing rural communities, in particular in mountain areas. The model proposed, with the elaboration of a management software and technical agronomic sheets, could be an incentive for the activities already present in that region and to stimulate new ones. The enhancing of the native ecological system, the biodiversity tutelage and the valorization of the knowledge of the territory is the basic requirement for the successful of any land management.

Agricultural Multifunctionality Evolution and Research into Issues concerning Agriculture,Countryside and Farmers

From the point of view of agricultural civilization, the history of human civilization is the history of the development of the agricultural civilization. Accompanied by social progress and development of the times, the function of agriculture also experiences the expansion and deepening. In terms of economy, there is a process from mechanized farming to industrialization, then to informatization, modernization and internationalization. The great rejuvenation of the Chinese nation has also experienced and witnessed this process. In terms of "agriculture, countryside and farmers", the content is complex, diverse, profound, sharp, and changing, constantly testing and challenging our wisdom. When the Document No.1 in 2007 targeted modern agriculture, it indicated that new connotation was integrated into agricultural multifunctionality, standing at a new starting point. At present, the function of agriculture is still deepening; there are tremendous achievements and outstanding problems concurrently in issues concerning agriculture, countryside and farmers. We take the agricultural multifunctionality as breakthrough point for exploration and research.

Autonomous Unmanned Aerial Vehicles Based Decision Support System for Weed Management

Recently,autonomous systems become a hot research topic among industrialists and academicians due to their applicability in different domains such as healthcare,agriculture,industrial automation,etc.Among the interesting applications of autonomous systems,their applicability in agricultural sector becomes significant.Autonomous unmanned aerial vehicles(UAVs)can be used for suitable site-specific weed management(SSWM)to improve crop productivity.In spite of substantial advancements in UAV based data collection systems,automated weed detection still remains a tedious task owing to the high resemblance of weeds to the crops.The recently developed deep learning(DL)models have exhibited effective performance in several data classification problems.In this aspect,this paper focuses on the design of autonomous UAVs with decision support system for weed management(AUAV-DSSWM)technique.The proposed AUAV-DSSWM technique intends to identify the weeds by the use of UAV images acquired from the target area.Besides,the AUAV-DSSWM technique primarily performs image acquisition and image pre-processing stages.Moreover,the Adam optimizer with You Only Look Once Object Detector-(YOLOv3)model is applied for the detection of weeds.For the effective classification of weeds and crops,the poor and rich optimization(PRO)algorithm with softmax layer is applied.The design of Adam optimizer and PRO algorithm for the parameter tuning process results in enhanced weed detection performance.A wide range of simulations take place on UAV images and the experimental results exhibit the promising performance of the AUAV-DSSWM technique over the other recent techniques with the accy of 99.23%.

Digital twins in smart farming:An autoware-based simulator for autonomous agricultural vehicles

Digital twins can improve the level of control over physical entities and help manage complex systems by integrating a range of technologies.The autonomous agricultural machine has shown revolutionary effects on labor reduction and utilization rate in field works.Autonomous vehicles in precision agriculture have the potential to improve competitiveness compared to current crop production methods and have become a research hotspot.However,the development time and resources required in experiments have limited the research in this area.Simulation tools in unmanned farming that are required to enable more efficient,reliable,and safe autonomy are increasingly demanding.Inspired by the recent development of an open-source virtual simulation platform,this study proposed an autoware-based simulator to evaluate the performance of agricultural machine guidance based on digital twins.Oblique photogrammetry using drones is used to construct threedimensional maps of fields at the same scale as reality.A communication format suitable for agricultural machines was developed for data input and output,along with an inter-node communication methodology.The conversion,publishing,and maintenance of multiple coordinate systems were completed based on ROS(Robot Operating System).Coverage path planning was performed using hybrid curves based on Bézier curves,and it was tested in both a simulation environment and actual fields with the aid of Pure Pursuit algorithms and PID controllers.

基于农机智能管理平台的田间燃油配给策略

在农业规模化生产中,为保证作业效率,农机燃油配给往往需要在田间完成。然而,现有的田间燃油配给方式存在不安全、不及时、缺乏科学系统的配给决策,导致燃油配给效率低、配送成本高等问题。针对上述问题,该研究结合农机燃油需求特点,提出基于农机智能管理平台的农机田间燃油配给策略。首先,以农机智能管理平台的实时数据为基础,基于可信性理论建立农机田间燃油配给的两阶段数学模型:第一阶段预优化,根据平台数据建立具有模糊需求和模糊时间窗的多目标车辆路径规划模型,第二阶段根据实际生产中发生的动态事件更新相关信息,重新规划未配送订单的配送路径;其次,以总配送成本最低及总满意度最高为目标,结合改进遗传算法求解农机田间燃油配给模型。最后,应用嫩江农场的数据进行实证分析,并与农场当前的配送成本等指标进行对比,验证可行性及实用性。结果表明:基于农机智能管理平台实时数据构建的农机田间燃油配给策略可以在降低配送成本的同时,保证较高的订单平均满意度,即时效性,与当前生产方案相比,配送路径减少了14条,虽然满意度较实际稍低,为72.85%,但总配送成本较当前方案降低了93.38%。研究结果可为农机田间燃油配给的智能化管理提供科学依据。

电动智能农业车辆开发技术与现状

为提高从业人员对电动智能化农业车辆现阶段技术状况的认知水平,本文从电动化、智能化两个方向进行调研、分析了电动智能农业车辆在电驱动、动力电池、智能网联等技术方面的国内外发展概况。经过对大量文献进行分析,中国电动智能化农业车辆存在起步晚、技术落后、产业化程度滞后等问题,中国在电驱动技术、电池技术、网联化技术等方面还有较大的研发空间。

改进猫群算法在车辆配送路径优化中的应用研究

为解决在生鲜农产品的车辆配送过程中存在的成本高、碳排放高的问题,以顾客满意度最高和总配送成本最低为目标,构建低碳冷链生鲜农产品的车辆配送路径优化模型。首先,通过多种方法对猫群算法进行优化;然后,用优化的猫群算法对模型进行求解。通过仿真实验对车辆配送路径优化前后效果进行分析,验证了所构建模型的可行性。结果表明,所构建的模型能有效地解决车辆配送的路径优化问题;与传统车辆配送的路径规划方法相比,采用所构建的车辆路径优化模型,车辆配送总路径和碳排放量都有一定程度的改善;车辆总配送路径长度缩短了489.77km、车辆碳排放量降低了21.4%。该方法能有效降低车辆配送过程的总成本和碳排放量,可在一定程度上提高车辆的利用效率和物流企业的市场竞争力。

基于ASTUKF的分布式农业车辆路面参数辨识方法

针对分布式驱动农业车辆在路面参数辨识过程中,因路面环境变化出现的状态模型误差和时变噪声,导致辨识结果发散的问题,提出了基于自适应强跟踪无迹卡尔曼滤波(Adaptive strong tracking unscented Kalman filter,ASTUKF)的辨识方法。与传统内燃机农业车辆相比,分布式驱动可以直接获取驱动轮的状态信息,结合含有峰值附着系数和极限滑转率的μ-s曲线模型,建立了无迹卡尔曼滤波(Unscented Kalman filter,UKF)辨识算法的状态方程和量测方程。同时,将强跟踪滤波(Strong tracking filter,STF)和自适应滤波(Adaptive filter,AF)引入辨识算法,用以提高对多变环境的识别精度和鲁棒性,并采用奇异值分解(Singular value decomposition,SVD)解决了迭代过程中出现的非正定矩阵的问题。仿真试验结果表明,在突变噪声环境工况下,ASTUKF辨识结果可以快速收敛至目标值附近,且不受突变噪声的影响,各驱动轮峰值附着系数估计结果的平均绝对误差(Mean absolute error,MAE)分别为0.0144、0.0267、0.0144、0.0267,极限滑转率估计结果的MAE分别为0.0025、0.0028、0.0025、0.0028。实车试验表明,在已耕地和未耕地的试验路面上,ASTUKF辨识结果的均值95%置信区间能够匹配测量值,整车的附着系数辨识结果为0.4061(未耕地)、0.3991(已耕地),极限滑转率辨识结果为0.1484(未耕地)、0.3600(已耕地),可为分布式电动农业车辆作业参数感知提供理论参考。

生鲜农产品车辆和无人机组合配送路径优化及效果测试

【目的】为提升生鲜农产品的配送效率,提出生鲜农产品车辆与无人机组合配送路径优化方案。【方法】按照生鲜农产品冷链配送体系要求,采用模糊K-means聚类方法确定生鲜农产品配送中心;定义配送中心位置为车辆和无人机组合配送的起点,以生鲜农产品配送总成本最小为目标函数,利用蚁群算法和无人机物流车协调配送算法求解上述构建的目标函数,获取最低配送总成本的配送路径规划结果;引入安全启发函数优化蚂蚁转移规则,获取安全最高的无人机最优配送路径。再按照该方法,将生鲜农产品按照质量划分为重件和轻件,并计算重件和轻件在配送过程中产生的成本,获取在不同的总配送生鲜农产品快件数量下,优化前与优化后的配送成本。【结果】效果测试表明,该方法具有良好的聚类效果,簇类凝聚度(Davies-Bouldin, DB)指数值均低于0.15,可合理选取配送中心,保证配送中心的覆盖程度。并且通过对比该方法应用前后的数据对比可知,应用前重件和轻件的配送成本明显更高于应用后的成本。【结论】该方法可以更高质量地完成车辆和无人机组合配送路径规划,能够显著降低生鲜农产品的配送总体成本,应用效果满足应用需求,提升配送效率。

Discussion on Structure Evolution and Function Expansion of Agriculture in China

According to the characteristics of agricultural development during different periods, agricultural development was basically divided into traditional period, planning system period and household contracting pedod to discuss the related laws of agricultural development in China. The agricultural function expansion during different periods was analyzed in terms of agricultural structure evolution, while structural optimization and function expansion of modem agriculture in China were also studied. The results indicated that during the traditional period, agricultural structure emphasized feeding people and grain production while agricultural function reflected the economic function beyond surviving standard. During the planning system period, a unitary structural mode of agriculture was formed in China, which showed that agriculture was dominated by planting industry and planting industry was dominated by grain, while agriculture executed the mixed economic function beyond surviving and liv- ing standard. During the household contracting period, the industrial structure of agriculture in China gradually became diversification and optimi- zation, but as the economic function of industrial standard, agricultural development was still greatly inhibited. The structural evolution of modem agriculture in China must step forward towards collectivization and scale merit, while ecological function and social function of agriculture increas- ingly become important and the function of agricultural production becomes mere and more diverse.

基于MPC延时补偿器的农机多机器人编队行驶轨迹跟踪方法

[目的/意义]农机装备尺寸大、行驶慢等特点,在路面归库作业过程中容易造成严重道路拥堵。因此,在多机协同过程中,编队行驶被认为是未来道路上行驶的主要方式。然而,目前农机自动驾驶技术停留在单机阶段,多农机之间的协同仍是制约中国农业规模化自主生产的主要瓶颈。为解决多车编队协同控制中通信延时的问题及其补偿策略,本研究基于一种模型预测控制器(Model Predictive Control,MPC)延时补偿器的农机多机编队行驶的轨迹跟踪方法。[方法]以车联网技术为基础,聚焦多农机编队协同控制领域,针对控制器局域网总线(Controller Area Network,CAN)通信存在的延时问题而产生的横向控制精度差,基于线性二次调节器(Linear Quadratic Regulator,LQR)与MPC算法,设计了一种带有延时补偿的模型预测控制器,用于对通信延时进行补偿控制。最后对所提算法利用Carsim和Simulink软件进行联合仿真。[结果和讨论]Carsim与MATLAB/Simulink可以有效兼容,实现软件与外部求解器的联合仿真。当延时步长d=5时,应用延时补偿,MPC反应速度更快,表现更为平滑;速度误差曲线响应更快,且能够逐渐稳定至零误差,没有出现振荡现象;1号车在较短时间内有效地变更车道,与头车保持在同一车道上。在更长的延时步长d=10情况下,未应用延时补偿的控制器表现出更显著的性能下降。即使在较高的延时条件下,应用延时补偿的MPC速度误差和纵向加速度仍然能够快速响应并逐渐稳定至零误差,避免了振荡现象。1号车的轨迹表明,延时补偿机制效果在极端延时条件下有所下降。[结论]本研究所设计的编队算法能够使得多车完成多车变道形成队列并保持一定距离和一定速度。通信延时补偿控制算法使得带有加入延时的车辆能较好完成编队任务,实现稳定的横纵向控制,验证了本研究带有延时补偿的模型预测控制器的可行性。

基于ICR的履带车辆路径跟踪与转向控制算法研究

针对丘陵山区单边制动农用履带车辆路径跟踪精度低、控制次数多、转向偏差大等问题,本文开展不同负载条件下履带车辆路径跟踪控制研究。首先,对履带车辆的转向运动学进行理论分析,并建立履带车辆运动学模型;其次,根据履带车辆单边制动转向特性,提出一种基于瞬时旋转中心(Instantaneous center of rotation, ICR)的大角度转向控制算法,该算法能够根据规划路径的转向点位置与履带车辆转向瞬心,规划出最优的转向目标点,并控制履带车辆在该转向目标点一次性转向到所需航向,与此同时,完成转向控制器设计;最后,开展履带车辆在3种不同负载条件下的仿真试验与田间试验。仿真结果表明,大角度转向控制算法产生的跟踪路径平均误差面积与平均转向控制次数分别降低68.95%、68.77%;田间试验结果表明,大角度转向控制算法产生的跟踪路径平均横向偏差均值、平均转向控制次数与转向点处平均最小偏差分别减少57.27%、33.93%、62.29%,且路径跟踪效果更优,验证了大角度转向控制算法的有效性。试验结果满足履带车辆路径跟踪的要求,为实现农用履带车辆的路径跟踪提供理论基础与参考。

农业运输车自动导航系统的设计及试验研究

农业运输车在农业生产中承担着输送产品及运输物资的任务,目前其运输效率及路径计划主要依靠驾驶员的专业技能。农业运输车在进行田间谷物收获、合理调度及运输计划是保证农业运输车高效运行的重要因素,随着自动导航技术的逐渐应用及发展,实现农业运输车高效运输及路径规划具有重要意义。为此,创新研制了一种自主导航系统,将收获和运输问题视为一个带动态卫星的两级多行程车辆路径问题(2E-MTVRPDS),并进行自动导航系统的路径规划、地头转弯、控制系统、卫星传输及人机交互界面设计,以实现农业运输设备的路径自主规划与移动。以谷物联合收获机及拖拉机为试验对象,研究结果表明:当拖拉机完成直线导航时,会自动执行适当的转弯模式,直线跟踪的横向误差不超过6cm,直线跟踪最大横向均方根误差小于5cm,表明提出的农业运输车自动导航系统在引导农用车辆田间工作时具有通用性和良好的工作性能,可以满足田间农业生产要求。

新能源纯电动四驱农机电机控制系统研究

直流无刷电机因其效率高、寿命长和良好的动态特性,逐渐成为电动车辆的优先动力选择。为此,提出了一套基于TMS320F2812的纯电动四驱农机电机控制系统,采用直流无刷电机作为驱动器件,并结合增量式PI控制算法,实现了纯电动四驱农机电机的高精度控制。实际应用表明:该系统更适用于纯电动四驱农机复杂的运行工况。

机械弹性车轮的滚动模态特性研究

轮胎是农用车辆行走系的重要部件,直接影响车辆各种使用性能的发挥。针对传统农用车轮胎在使用过程中易扎伤、易磨损等问题,设计了一种新型机械弹性车轮。利用有限元方法结合LMS模态试验,研究了各种因素对机械弹性车轮模态参数的影响机理和规律,计算了滚动状态下机械弹性车轮的模态参数,获得了转速对车轮模态参数的影响规律,从而得到了滚动状态下机械弹性车轮的模态特性。研究结果表明,机械弹性车轮在滚动状态下的模态特性可为其与农业车辆的匹配提供一定的指导。

基于DQN算法的农用无人车作业路径规划

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农产品供应链是农产品流通现代化的重要体现。随着生活水平的提高,人们对生鲜农产品的需求逐渐增加,农产品供应链冷链配送压力不断增大,农产品包装也随之造成严重的环境污染。文章基于对包装二次利用的考虑,以车辆固定成本、车辆运输成本及制冷成本最小为目标,构建考虑客户满意度的两级生鲜农产品冷链车辆路径优化数学模型,融合变邻域搜索机制的离散哈里斯鹰算法对该模型进行求解,使用迭代贪心算法和随机方法生成初始解,然后使用设计的搜索算子寻优。通过仿真实验对提出算法与其他算法和数字优化技术(CPLEX)进行对比,验证了文章提出的改进哈里斯算法可行性、高效性及稳定性,对城市限行下农产品冷链配送路径优化问题研究具有一定的意义。