Data for MultiDLO: Simultaneous Shape Tracking of Multiple Deformable Linear Objects with Global-Local Topology Preservation

The MultiDLO data release supports the paper, "MultiDLO: Simultaneous Shape Tracking of Multiple Deformable Linear Objects with Global-Local Topology Preservation," presented in the IEEE International Conference on Robotics and Automation Workshop on Representing and Manipulating Deformable Objects in May 2023. The data release includes the raw image and depth data for simultaneously tracking multiple Deformable Linear Objects (DLOs). The released data are Robot Operating System (ROS1) bag files containing raw color images and point clouds. The data were collected using a static Intel Realsense d-435 RGB-D camera while DLOs in the field of view of the camera were manipulated. The data can be used to benchmark the performance of future DLO tracking or prediction algorithms in two manipulation scenarios relevant to DLOs and to verify existing DLO tracking algorithms. Please see the accompanying extended abstract, the code repository on GitHub, and the conference presentation video referenced in the `multidlo_data_release.pdf` document for more information.