Research On Path Planning And Obstacle Avoidance Method Of Agricultural Tractor

My country is a big agricultural country.With the promotion of the strict prohibition of straw burning,straw processing has become an important problem that needs to be solved urgently.As an important agricultural tool for straw leaving the field,the automatic operation of the baler can greatly Increase labor efficiency and save labor costs.Partial path planning and path tracking are important functions to realize the automatic operation of the baler,and are the basis for supporting agricultural machinery to complete field operations safely and stably in the changing farmland environment.In this context,this topic is based on the baler front drive tractor as an experimental platform to carry out related research on automatic driving.The main research contents are as follows:1)Combined with the research background,understand the related technologies of obstacle avoidance planning and motion control of agricultural machinery,analyze and compare the architecture and implementation forms of path planning and motion control systems in unmanned driving technology at home and abroad.In the perception part,the sensor is used to obtain the real-time information of the position of the agricultural machinery and the surrounding environment,and the kinematics model is established based on the characteristics of the agricultural machinery.2)An improved algorithm based on Rapid Search Random Tree(RRT)is proposed as a local path planning algorithm to achieve obstacle avoidance processing in farmland.In the improved RRT path planning algorithm,the vehicle is first combined with the path tracking process.The tracking error in the tracking error is expanded by obstacles,and then the redundant inflection points in the path points generated by the RRT algorithm are removed.Finally,the B-spline curve is used to fit the remaining path points,so that the planned path is smoother,and it is convenient for the agricultural machinery to operate in the farmland environment.walk in.And the effectiveness of the algorithm is verified by experiments.3)A path tracking control method based on BP neural network is proposed.The method dynamically adjusts the forward sight distance according to the vehicle speed,thereby determining the target point,and using the optimal control quantity output by the BP neural network as the control coefficient of the steering angle.,and then the final steering angle is determined by the positional relationship between the current position of the vehicle and the target point.The agricultural machinery is controlled by the steering angle of the front wheel to complete precise tracking.In the aspect of vehicle longitudinal speed control,the traditional PID control algorithm is used to make the vehicle track the desired speed.The simulation analysis of different path tracking algorithms proves the effectiveness of the proposed algorithm.4)The verification experiments on straight lines and curves were carried out,including the refinement of experimental conditions such as platform equipment,communication protocols,data processing methods,etc.,and the stability and applicability of the proposed algorithm were verified through the path tracking experiments of tractors in the field.,laying the foundation for the automation of field operations.