The automated detection of R. obtusifolius L. (broad-leaved dock) has been investigated in agricultural robotics from the early 2000s up until today. However, research groups have evaluated their work on their own, relatively small datasets. We aim to close that gap by making a new 30.3 GB large dataset—RumexWeeds—publicly available, enabling comparability of future approaches. RumexWeeds consists of image sequences with totally 5510 images of 2.3 MP resolution and 15,519 manual bounding box annotations collected at three different farms and four different days in summer and autumn 2021. Additionally, navigational robot sensor points from GNSS, IMU and odometry are recorded. The dataset is publicly available at https://dtu-pas.github.io/RumexWeeds/. In the accompaying paper (https://onlinelibrary.wiley.com/doi/10.1002/rob.22196), apart from introducing the RumexWeeds dataset, we also present detection as well as segmentation prediction results on it, which serve as baseline for the research community.

Links: https://dtu-pas.github.io/RumexWeeds/

Harness the possibilities that GALILEO brings to deliver robot weeding for herbicide-free weed control in dairy farming. Robotic weeding will eliminate herbicide use and reduce exposure of farm workers (remove obstacle for organic production). Broad-leaved dock (rumex obtusifolius) is a problematic weed that expands and cover large parts of the farm if uncontrolled.

Links: https://galirumi-project.eu/