Robust 6D Object Pose Estimation by Learning RGB-D Features

@article{Tian2020Robust6O,
  title={Robust 6D Object Pose Estimation by Learning RGB-D Features},
  author={Meng Tian and Liang Pan and Marcelo H. Ang and Gim Hee Lee},
  journal={2020 IEEE International Conference on Robotics and Automation (ICRA)},
  year={2020},
  pages={6218-6224}
}
  • Meng Tian, Liang Pan, +1 author Gim Hee Lee
  • Published 29 February 2020
  • Computer Science
  • 2020 IEEE International Conference on Robotics and Automation (ICRA)
Accurate 6D object pose estimation is fundamental to robotic manipulation and grasping. Previous methods follow a local optimization approach which minimizes the distance between closest point pairs to handle the rotation ambiguity of symmetric objects. In this work, we propose a novel discrete- continuous formulation for rotation regression to resolve this local-optimum problem. We uniformly sample rotation anchors in SO(3), and predict a constrained deviation from each anchor to the target… 
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