基于DSP和MCU的农机具视觉导航终端设计
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国家国际科技合作专项资助项目(2015DFG12280)、国家自然科学基金资助项目(31571570)和中央高校基本科研业务费专项资金资助项目(2015XD004)


Development of Agricultural Implement Visual Navigation Terminal Based on DSP and MCU
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    摘要:

    农机具导航可以提高作业的精度和适应性。针对当前导航终端多基于工控机开发,成本相对较高,不利于在农业生产中大规模推广等问题,设计了一种基于DSP和MCU的农机具视觉导航终端,用于玉米中耕锄草自动导航作业。其中,DSP作为核心处理器,负责农作物的图像采集、作物行检测和导航线提取;MCU负责作业流程的管理、GNSS位置信息的接收、存储和转发以及向执行单元发送控制指令等。针对导航终端中所涉及的串口、网络以及CAN总线之间的通信问题,制定了相应的协议规范;按照系统集成优化设计方法,构建了农机具视觉导航终端系统,保证了系统运行稳定性;对图像进行预处理后,采用基于边缘检测和扫描滤波的导航线检测算法提高了农机具导航线检测的精度和处理效率;针对农田玉米中耕锄草试验,设计了导航线算法适应性试验、偏移量测试试验和系统对比试验。结果表明:系统能够较好地适应有杂草和株数稀疏等农田环境下的测试工作;对偏移量检测的平均误差为1.29 cm,最大误差为4.1 cm;对比PC端和ARM端的导航算法运行速度,系统具有较好的实用性和经济可行性。

    Abstract:

    Agricultural implement automatic navigation is a major trend of modern agriculture. Agricultural implement navigation can avoid the errors during implement shaking in field and improve the precision of navigation and flexibility of operation. At present, most of the navigation terminals were developed based on the industrial computer which is expensive and difficult to be spread. In this paper, an agricultural implement visual navigation terminal based on DSP and MCU for automatic weeding was designed. As the core processor of the system, DSP was responsible for the image acquisition, crop rows detection and offset calculation of navigation line. MCU is the main control unit of the system, so it was used to manage the working process, receive, store and forward GNSS data, and also control the implement. The corresponding protocol of serial communication, network communication and CAN bus communication in the system was normalized to make sure the stability of the communication. In the image processing, the OTSU method and the crop row detection algorithm based on boundary detection and scan-filter (BDSF) were adopted, which could improve the accuracy and efficiency of navigation line detection. In order to verify the validity and stability of the system, the algorithm adaptive test, offset accuracy test and different system comparison tests were carried out. The experiment results showed that the crop line detection algorithm could work adaptively in the weed and crop thinning conditions. The average error of offset detection is 1.29 cm and the maximum error is 4.1 cm. The systems comparison test verified the economic feasibility of the proposed system by compared with the PC and ARM, which can satisfy the requirements of filed operation.

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项明,魏爽,何洁,仇瑞承,张漫.基于DSP和MCU的农机具视觉导航终端设计[J].农业机械学报,2015,46(S1):21-26. Xiang Ming, Wei Shuang, He Jie, Qiu Ruicheng, Zhang Man. Development of Agricultural Implement Visual Navigation Terminal Based on DSP and MCU[J]. Transactions of the Chinese Society for Agricultural Machinery,2015,46(S1):21-26

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  • 收稿日期:2015-10-28
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  • 在线发布日期: 2015-12-30
  • 出版日期: 2015-12-31