Progressive 3D reconstruction of unknown objects using one eye-in-hand camera

Walck, Guillaume; Drouin, M.

doi:10.1109/robio.2009.5420748

Cited by 3 publications

(1 citation statement)

References 28 publications

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“…However, the eye-in-hand vision system is more accurate than the visual odometer. Therefore, it is necessary to make full use of the high accuracy of the robotic manipulator to improve the quality of the 3D reconstruction of the scene [16,17]. Another problem is that the precision of semantic segmentation is still insufficient, even by the latest method, so it is necessary to find a way to improve the quality of semantic segmentation.…”

Section: Introductionmentioning

confidence: 99%

Semantic 3D Reconstruction for Robotic Manipulators with an Eye-In-Hand Vision System

Zha

Wang

et al. 2020

Applied Sciences

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Three-dimensional reconstruction and semantic understandings have attracted extensive attention in recent years. However, current reconstruction techniques mainly target large-scale scenes, such as an indoor environment or automatic self-driving cars. There are few studies on small-scale and high-precision scene reconstruction for manipulator operation, which plays an essential role in the decision-making and intelligent control system. In this paper, a group of images captured from an eye-in-hand vision system carried on a robotic manipulator are segmented by deep learning and geometric features and create a semantic 3D reconstruction using a map stitching method. The results demonstrate that the quality of segmented images and the precision of semantic 3D reconstruction are effectively improved by our method.

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Section: Introductionmentioning

confidence: 99%