An approach to the vision tasks involved in an autonomous crop protection vehicle

Abstract This paper presents an approach to the vision tasks to be performed in a vehicle navigation application in crop fields. The objective is to automate chemical spraying by means of autonomous navigation and machine vision. A camera is used as the sensor device, and a bar of spraying nozzles is provided to perform the spraying. The proposed solution consists of recovering maps of the environment from the image sequence, and exploring them to locate the path to be followed and the nozzles that have to be switched on. The motion parameters of the vehicle are used to place the images in the map, and are computed from a feature-tracking method. The plants and the weeds are identified through segmentation, and the features to be tracked are computed from the contours of the plants. Results, with real image sequences of all the steps involved, are presented.

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