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Johnson-Roberson, Matthew
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Engineering
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- Creator:
- Billings, Gideon H and Johnson-Roberson, Matthew
- Description:
- UWslam is a dataset for underwater stereo and hybrid monocular fisheye + stereo SLAM in natural seafloor environments. The dataset includes a spiral survey of a shallow reef captured with a diver operated stereo rig and 4 hybrid image sequences captured with a deep ocean ROV in different deep ocean environments. Ground truth pose estimates for the spiral stereo trajectory were obtained by processing the image sequence through COLMAP. Ground truth pose estimates for the hybrid sequences were obtained by distributing fiducials on the seafloor before capturing an image sequence and processing the image sequences with the ROS based TagSLAM package.
- Keyword:
- SLAM, Simultaneous Localization and Mapping, Visual Reconstruction, and Underwater
- Citation to related publication:
- G. Billings, R. Camilli and M. Johnson-Roberson, "Hybrid Visual SLAM for Underwater Vehicle Manipulator Systems," in IEEE Robotics and Automation Letters, vol. 7, no. 3, pp. 6798-6805, July 2022, doi: 10.1109/LRA.2022.3176448.
- Discipline:
- Engineering
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- Creator:
- Billings, Gideon H and Johnson-Roberson, Matthew
- Description:
- UWHandles is a dataset for 6D object pose estimation in underwater fisheye images. It provides 6D pose and 2D bounding box annotations for 3 different graspable handle objects used for ROV manipulation. The dataset consists of 28 image sequences collected in natural seafloor environments with a total of 20,427 annotated frames. and Meta repository for the dataset https://github.com/gidobot/UWHandles
- Keyword:
- Deep Learning, Pose Estimation, and Underwater Vision
- Citation to related publication:
- Billings, G., & Johnson-Roberson, M. (2020). SilhoNet-fisheye: Adaptation of a ROI based object pose estimation network to monocular fisheye images. IEEE Robotics and Automation Letters, 5(3), 4241-4248.
- Discipline:
- Engineering
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- Creator:
- Kim, Wonhui, Ramanagopal, Manikandasriram Srinivasan, Barto, Charles , Yu, Ming-Yuan, Rosaen, Karl , Goumas, Nick , Vasudevan, Ram, and Johnson-Roberson, Matthew
- Description:
- PedX is a large-scale multi-modal collection of pedestrians at complex urban intersections. The dataset provides high-resolution stereo images and LiDAR data with manual 2D and automatic 3D annotations. The data was captured using two pairs of stereo cameras and four Velodyne LiDAR sensors.
- Citation to related publication:
- https://doi.org/10.48550/arXiv.1809.03605, https://github.com/umautobots/pedx, and http://pedx.io/
- Discipline:
- Engineering