Learning-driven coarse-to-fine articulated robot tracking
In this work we present an articulated tracking approach for robotic manipulators, which relies only on visual cues from colour and depth images to estimate the robot’s state when interacting with or being occluded by its environment. We hypothesise that articulated model fitting approaches can only...
| Главные авторы: | , , , , |
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| Формат: | Conference item |
| Опубликовано: |
IEEE
2019
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