Research On Complete Coverage Path Planning For Intelligent Agricultural Machinery

The advancement of society and technology has promoted the development of modern agriculture.It has become a trend to replace traditional manpower with intelligent agricultural machinery that operates independently.As the core technology of intelligent agricultural machinery,complete coverage path planning technology has become more important.At present,the complete coverage path planning used by robots still suffers from problems such as sacrificing the coverage rate to obtain the minimum energy consumption,taking a long time to calculate the algorithm,and crossing the covered region;these problems mean that robots cannot completely meet the needs of current agricultural machinery operations.Therefore,aiming at the operating region characteristics and path planning requirements of intelligent agricultural machinery,this paper carried out the environmental modeling of intelligent agricultural machinery and the design and experimental analysis of complete coverage path planning methods.The main contents are as follows:(1)Aiming at the intelligent agricultural machinery,this paper designed an environment modeling method and a regional division strategy.Through the analysis and comparison of the commonly used environmental modeling methods,an environmental modeling method based on the cell decomposition method was selected and constructed.This paper abstracted the intelligent agricultural machinery as a mass point,and expanded the boundary and obstacles while considering the safety factor.The distance was superimposed on the boundary and the edge of obstacles to ensure the safety of intelligent agricultural machinery.Aiming at the complex environment,a regional division strategy based on Morse decomposition was designed and implemented.Through modeling and optimization analysis of operation energy consumption,a round-trip path coverage method that walks along the long side was proposed to achieve complete coverage of local sub-regions.(2)Aiming at connection problem between sub-regions,a regional connection strategy based on the known environment was designed and implemented.In this strategy,a backtracking mechanism was established by combining the greedy algorithm with the Manhattan distance formula,which was used to record uncovered sub-regions and select the best backtracking point in the process of regional connection.Then,designed the algorithm of regional connection path planning.Aiming at the work environment with obstacle,in order to avoid the omission of coverage and the second crossing of the traversed region,which will damage the crops that have been planted in the farmland,this paper proposed a priority walking strategy in the middle region.In order to avoid crossing the traversed region in the process of traversing to the next region,this paper proposed a strategy of walking along the boundary.The two strategies proposed in this paper can reduce the repeated coverage rate and improve the performance of the current complete-coverage path planning method.Finally,this paper integrated the above strategies,and constructed a complete-coverage path planning method for intelligent agricultural machinery based on the improved backtracking method.(3)In order to verify the effectiveness of the complete coverage path planning method based on the improved backtracking method,a simulation experiment was designed and the experimental analysis was completed.First,this paper selected farmland in Changfeng and Lujiang on Google Maps as the experimental objects.Then,the environment coordinate system was constructed based on Gaussian projection,and the coordinate system was mapped according to the working direction,which provided a reasonable mathematical environment model for the research of intelligent agricultural machinery path planning.Finally,the algorithm proposed in this paper and the traditional backtracking method were individually simulated,and the experimental results were compared and analyzed.The results show that the method has the advantages of faster calculation speed,lower repetition rate,and reduced crossing region,which proves the optimization of the path planning method and the effectiveness of actual application,and saves the energy consumption and the cost of operation.The research in this paper will provide technical support for agricultural operations such as sowing,tillage and harvesting in agricultural production,and improve the quality and efficiency of intelligent agricultural machinery.