YOLOX-based blue laser weeding robot in corn field.

Huibin Zhu, Yuanyuan Zhang, Danlei Mu,Lizhen Bai, Hao Zhuang,Hui Li

Frontiers in Plant Science(2022)

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摘要
A YOLOX convolutional neural network-based weeding robot was designed for weed removal in corn seedling fields, while verifying the feasibility of a blue light laser as a non-contact weeding tool. The robot includes a tracked mobile platform module, a weed identification module, and a robotic arm laser emitter module. Five-degree-of-freedom robotic arm designed according to the actual weeding operation requirements to achieve precise alignment of the laser. When the robot is in operation, it uses the texture and shape of the plants to differentiate between weeds and corn seedlings. The robot then uses monocular ranging to calculate the coordinates of the weeds using the triangle similarity principle, and it controls the end actuator of the robotic arm to emit the laser to kill the weeds. At a driving speed of 0.2 m·s -1
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关键词
deep learning,laser weeding,weed recognition,weeding robot,Yolo algorithm
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