Andreas Michaels

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This paper proposes a machine vision approach for plant classification without segmentation and its application in agriculture. Our system can discriminate crop and weed plants growing in commercial fields where crop and weed grow close together and handles overlap between plants. Automated crop / weed discrimination enables weed control strategies with(More)
This paper describes the control aspects and results of a student project called “MonoChair”. The goal was to have students walk through a complete control systems development cycle. The focus in this contribution is put on the design of a stabilizing linear controller, a sensitivity analysis in order to study the impact of parameter(More)
In this system paper we present a novel approach for autonomous, mobile manipulation for agricultural robots. Our target application is mechanical weed control which for example is needed in organic farming. Today, this task is often performed by field workers, whose availability is declining and the quality of their work differs greatly. In addition,(More)
The collaborative research project RemoteFarming.1 integrates innovative agricultural engineering (field robotics, sensors, actuators) and web-based communication technologies. It aims to develop a robotic weed control system which integrates a human user as remote worker in the process. Thus, it drastically reduces the complexity of the problem in(More)
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