Research On The Path Planning And Control Methods Of Feeding Machinery In Large-scale Meat Sheep Farms

Smart animal husbandry is an inevitable trend in the development of animal husbandry today,and it is the only way to promote the rapid development of animal husbandry production and achieve scale and industrialization.The autonomous navigation and driving system of vehicles provides important technical support for it.Taking the feeding and feeding operation of Xinjiang sheep breeding as the research object,it focuses on the research of navigation operation path recognition and planning algorithm,path fitting and vehicle positioning algorithm,steering control algorithm and steering actuator.Design a set of vehicle autonomous navigation driving system suitable for self-propelled agitating feeders in large-scale meat sheep breeding plants to improve the operation quality,reduce labor intensity,and reduce the risk of zoonotic diseases.The main research contents are as follows:(1)Navigation operation path identification and planning algorithm design and experiment.Based on RGB color space,a path recognition algorithm based on RGB sample database is proposed.By collecting images of navigation operation paths under various working conditions,a sample database Model[][][](three-dimensional array)is constructed,and data processing and correction are performed on it,and test verification is carried out.The test results show that the algorithm has good performance.Strong environmental adaptability and accuracy.Combined with the location distribution of the plant area,a dynamic real-time path planning algorithm oriented at the target point is designed and simulated.The simulation results show that the designed path planning algorithm can effectively identify the turning action of the intersection and guide the vehicle operation to satisfy the vehicle.Autonomous navigation operation path planning requirements.(2)Design and experiment of visual navigation path fitting and vehicle positioning algorithm.Aiming at the problem of navigation operation path fitting,a one-way path fitting algorithm based on quadratic test of feature points is designed.Separate the cross paths using the cross path separation method,and use the one-way path fitting method to fit them.The test results show that the accuracy of the navigation operation path recognition is more than 99%,of which the detection time of the one-way path is 17?18 ms,and the detection time of the cross path is 29?31 ms.Aiming at the vehicle positioning problem,the vehicle position acquisition equation is constructed according to the imaging rule of the CCD camera and the vehicle position measurement test is carried out.The test results show that the measurement error of the heading angle is 1.50 at the maximum,and the measurement error of the position deviation is 2 cm at the maximum.(3)Design and trial production of steering control system.Taking the stepping motor as the power source and adopting the gear transmission method,a gear steering actuator is designed,and the hardware system is designed based on the 51 single chip microcomputer.Aiming at the vehicle steering control problem,on the basis of the constructed vehicle motion model,a PI compensation straight line control algorithm and a turn prediction algorithm based on path prediction are designed respectively.(4)Trial production and test of vehicle autonomous navigation driving system test platform.Taking the self-propelled agitating feeder as the test object,a test platform for vehicle autonomous navigation and driving system is built,and a field simulation test is conducted at the navigation test site of the factory in North Campus of Shihezi University in Xinjiang.The test results are as follows1)The straight line tracking errors of the vehicles running at slow one,slow two,and slow three speeds are 2.5 cm,3.6 cm,and 4.9 cm,respectively,which meets the navigation control accuracy requirements of each corresponding operation link of the vehicle,It laid the foundation for the autonomous navigation operation of the self-propelled mixing feeder.2)When the vehicle is driving at a slower speed,it can independently complete the auto-turning action.The turn control error range is 9.3 cm,which can meet the accuracy requirements of vehicle autonomous navigation and turn control under a predetermined path.Within the controllable range of linear navigation control,it meets the requirements of vehicle turning control3)The vehicle's autonomous navigation and driving system can accurately locate and recognize the steering intersection and execute the corresponding steering action.The execution accuracy of the steering action instruction is 100%,which meets the accuracy requirements for the execution of the steering action instruction of the vehicle's autonomous navigation operation.