A Dataset for Improved RGBD-Based Object Detection and Pose Estimation for Warehouse Pick-and-Place

@article{Rennie2016ADF,
  title={A Dataset for Improved RGBD-Based Object Detection and Pose Estimation for Warehouse Pick-and-Place},
  author={Colin Rennie and Rahul Shome and Kostas E. Bekris and Alberto Ferreira de Souza},
  journal={IEEE Robotics and Automation Letters},
  year={2016},
  volume={1},
  pages={1179-1185}
}
An important logistics application of robotics involves manipulators that pick-and-place objects placed in warehouse shelves. A critical aspect of this task corresponds to detecting the pose of a known object in the shelf using visual data. Solving this problem can be assisted by the use of an RGBD sensor, which also provides depth information beyond visual data. Nevertheless, it remains a challenging problem since multiple issues need to be addressed, such as low illumination inside shelves… CONTINUE READING
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