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Pose Estimation
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In order to manipulate an object, a robot must be able to estimate the pose of the target relative to itself.
Pose estimation processes input camera images to infer the 6-DoF pose of the target object in the scene.

Deep learning models have revolutionized pose estimation over classical techniques.
DNN models with architectures such as `DOPE (Deep Object Pose Estimation) <https://docs.nvidia.com/isaac/archive/2020.2/packages/object_pose_estimation/doc/dope.html>`__ and `CenterPose <https://github.com/NVlabs/CenterPose>`__
from NVIDIA Research can be trained with monocular camera images of real-world objects to estimate the pose of the object in a novel scene with relatively high accuracy.


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