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Crop Row Detection in Maize for Developing Navigation Algorithms Under Changing Plant Growth Stages

机译:玉米作物行检测在改变植物生长阶段下发展导航算法

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To develop robust algorithms for agricultural navigation, different growth stages of the plants have to be considered. For fast validation and repeatable testing of algorithms, a dataset was recorded by a 4 wheeled robot, equipped with a frame of different sensors and was guided through maize rows. The robot position was simultaneously tracked by a total station, to get precise reference of the sensor data. The plant position and parameters were measured for comparing the sensor values. A horizontal laser scanner and corresponding total station data was recorded for 7 times over a period of 6 weeks. It was used to check the performance of a common RANSAC row algorithm. Results showed the best heading detection at a mean growth height of 0.268 m.
机译:为农业导航制定强大的算法,必须考虑植物的不同增长阶段。为了快速验证和算法的可重复测试,数据集由一个带有不同传感器帧的4轮式机器人记录,并通过玉米行引导。通过总站同时跟踪机器人位置,以精确参考传感器数据。测量植物位置和参数以比较传感器值。横向激光扫描仪和相应的总站数据在6周内记录7次。它用于检查公共RANSAC行算法的性能。结果表明,平均生长高度为0.268米的最佳前置检测。

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