Abstract
This paper deals with robotic mechanical weed regulation in organic farming, particularly for carrot cultivation. For that purpose the autonomous agriculture robot ‘BoniRob’ is utilized which is the result of a predecessor project and which allows an ‘App’-concept with changing sensor/actuators arrangements to cope with different use cases.The perception and navigation system is based on semantic localization. It enables adaptation to different environmental conditions encountered in typical tasks. The paper illustrates how this system will now be employed for the task of mechanical weed control. Additionally, the system architecture is described including means to increase robustness and preventing undesirable system conditions. In order to ensure a robust task fulfillment in weed control a shared autonomy approach is proposed which combines an efficient collaboration of the autonomous robot with human interaction via immersion technologies. Further, the paper sketches the ongoing development of the weed manipulator which needs to operate in harsh environments and which is faced with challenging requirements from speed and accuracy perspective. A parallel-kinematic structure enhanced by computer vision and visual servoing is proposed to cope with the requirements. Finally, the paper presents our first results regarding the selection of the actuator principle.
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Notes
- 1.
Public funded project by BMELV (Federal Ministry of Food, Agriculture and Consumer Protection); project partners: Amazone, Bosch, Hochschule Osnabrück.
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Michaels, A. et al. (2012). Approach Towards Robotic Mechanical Weed Regulation in Organic Farming. In: Levi, P., Zweigle, O., Häußermann, K., Eckstein, B. (eds) Autonomous Mobile Systems 2012. Informatik aktuell. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32217-4_19
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