The Constructor Robotics group contributed within the EU-project “Cognitive autonomous diving buddy (CADDY)” to the development of methods for the machine perception of divers (see, e.g.,  ) in the context of Underwater Human Machine Interaction (U-HRI) . This included among others the collection of data for diver pose estimation.
The CADDY Underwater Diver Pose Dataset  consists of 12,000 stereo pair images synchronized with diver body pose measurements from a suit of Inertial Measurement Units (IMUs) on the diver’s body called DiverNet .
 A. G. Chavez, A. Ranieri, D. Chiarella, and A. Birk, “Underwater Vision-Based Gesture Recognition: A Robustness Validation for Safe Human-Robot Interaction,” IEEE Robotics and Automation Magazine (RAM), vol. 28, pp. 67-78, 2021. https://doi.org/10.1109/MRA.2021.3075560 [Preprint]
 A. G. Chavez, A. Ranieri, D. Chiarella, E. Zereik, A. Babic, and A. Birk, “CADDY Underwater Stereo-Vision Dataset for Human-Robot Interaction (HRI) in the Context of Diver Activities,” Journal of Marine Science and Engineering (JMSE), spec.iss. Underwater Imaging, vol. 7, 2019. https://doi.org/10.3390/jmse7010016 [Open Access]
 A. G. Chavez, C. A. Mueller, A. Birk, A. Babic, and N. Miskovic, “Stereo-vision based diver pose estimation using LSTM recurrent neural networks for AUV navigation guidance,” in IEEE Oceans, Aberdeen, UK, 2017. https://doi.org/10.1109/OCEANSE.2017.8085020 [Preprint]