水稻收获转运双机协同自主作业策略与试验

针对水稻收获机与转运车双机协同自主作业环节多、粮食转运过程复杂等问题，该研究设计了一种基于有限状态机（Finite State Machine，FSM）的水稻收获机与转运车协同作业策略，分析了水稻收获机与转运车协同作业模式，建立有限状态机模型。首先，基于作业环节设计触发条件、评估方法和执行流程等基础模块；然后，根据双机协同的各项状态建立状态信息矩阵；最后，依据协同触发事件与状态转移的逻辑设计状态转移链。构建协同作业时分复用控制逻辑框架，并运用Stateflow软件进行仿真分析，为验证所设计策略的田间实际作业效果，搭建了履带式水稻收获转运双机协同试验系统，收获速度为0.8 m/s，收割幅宽1.9 m，共28条收获边，协同路径选择在短边的机耕道上，连续协同工作时间大于等于120 min，采用套圈路径自主收获0.7 hm2水稻，期间共进行6次自动协同转运作业，将所收获的粮食转运到卡车上。试验结果表明，该策略可以实现水稻收获/卸粮转运自主作业，收获效率为0.35 hm2/h，为实现水稻收获双机智能转运协同功能奠定了基础，可为水稻无人农场建设提供技术支持。

Cooperative autonomous operation strategy and experiment of the rice harvester together with a rice-transporting vehicle

Many links and complex cooperative operations have posed a great challenge to the autonomous harvesting between rice harvester and transfer vehicle. In this study, a cooperative operation strategy was designed for the autonomous rice harvester and transfer vehicle using Finite State Machine (FSM). The cooperative mode was then divided into four links: independent harvesting, waiting for calls, cooperative truck unloading grain, and transportation. An FSM model was also established to construct the basic components of a collaborative harvesting state machine. After that, the state information matrix was defined to design the specific flow of basic action execution, including the harvester starts harvesting, stops harvesting, starts unloading grain and stops unloading grain. The transfer vehicle was then driven at the waiting point to cooperate with the alignment, then to start or stop grain unloading. As such, the state transition chain of collaborative work was constructed to clarify the transition relationship and trigger conditions between the states in the process of collaboration. The cooperative control logic framework involved the harvester and transfer vehicle, according to the state transition chain architecture. Stateflow tool was selected to simulate and verify the compiled logic framework in the MATLAB platform. The sequential execution was also simplified to introduce the timing and signal transmission delay of internal execution. The simulation results show that the states of the harvester and transfer vehicles were transferred orderly, particularly with the correct conversion of the trigger signal. The test results also show that the control logic strategy performed better for cooperative harvesting. A crawler-type rice collaborative harvesting system was constructed to verify the actual operating performance of the logic strategy, including the crawler rice harvester (Weichai Lovol Heavy Industry RG70V4G-014) and crawler rice transfer vehicle (Weichai Lovol Heavy Industry RG70V4G-015). Among them, the two intelligent agricultural machines adopted the fully electronically controlled chassis with the wire-controlled clutch, header, grain cylinder, and crawler driving system. The dual antenna BDS positioning system (Sina K726) was also equipped, where the data transfer unit (USR-G781) was used in the communication between two computers in the fixed-point cooperative experiment of rice harvesting. The 4/5 G data transfer unit (DTU) with human cloud was adopted at the same time. The autonomous control module was communicated with the control terminal through RS-232. A Self-control terminal (eAgri-800-RS) was installed in the two computers for the harvesting self-control, which communicated with the chassis Electronic Control Unit of the two computers through CAN bus. The software system was developed by Keil uVision 5. The linear path tracking was adopted to follow the model control in the navigation system. The two-computer alignment control was adopted to deal with the position error PID. The collaborative system test was carried out in the Zengcheng Experimental Base of South China Agricultural University. The harvester and transfer vehicle were designed to independently work in the field from the hangar of the base. Specifically, the harvesting speed and width were set at 0.8 m/s, and 1.9 m, respectively. The continuous cooperative working time was more than 120 min. 0.73 hm2 of rice were automatically harvested by the ferrule path. Six operations of the automatic cooperative transfer system were carried out to transfer the grain to the truck during this period. The transfer truck waited on the tractor road, and then transferred the harvested grain to the roadside truck, according to the designed fixed-point cooperative operation strategy. The harvester and transfer vehicle returned to the hangar in sequence after harvesting the whole farmland. The harvest and transportation path were also designed in the test plan. Among them, the specific harvesting path was designed to cover the field, where the outer ring was harvested first and then parallel rings, according to the size of the field. The cooperative path was selected on the short-side tractor road. A balance was obtained on the short-side straight-line paths of the harvesting operation. The transfer vehicles only needed to plan a reusable path. The grain alignment transfer work was completed to advance or reverse this path in the whole field. The specific transfer points were calculated from the coordinates issued by the harvester, all of which were located on this path. Consequently, the fixed-point cooperative operation was also realized using the autonomous harvester and the transfer vehicle, according to the predetermined path. The logic signals were successively recorded to normally trigger during network communication under the predetermined logic framework in the test. The whole cooperative process was aligned accurately to successfully complete the fixed-point cooperative harvesting operation and return to the hangar. Therefore, the cooperative operation strategy of double machines for rice harvesting was effective and reliable under the configuration, and the harvesting efficiency was 0.35 hm2/h. The finding can also provide strong support for the cooperative operation of autonomous full coverage harvesting in rectangular rice regions.