Advances in world modeling for agri-food robotics (eBook, PDF)

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Performing tasks in the agri-food industry can be complex due to the organic, unstructured environments and natural variation in product. Successfully implementing robotic systems in such contexts is highly dependent on their capacity to adapt to variability, unpredictability and incomplete sensor data. Given the multitude of potential unexpected scenarios, it is no longer satisfactory to create fixed plans and controllers for the robot to address a task. Instead, it is essential to model our knowledge of the task and of the robot's operating environment, which is the central concept referred ...

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