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基于VDB数据结构的层次化、密集型和动态3D重建在机器人操作任务中的应用

Hierarchical, Dense and Dynamic 3D Reconstruction Based on VDB Data Structure for Robotic Manipulation Tasks.

作者信息

Mateo Carlos M, Corrales Juan A, Mezouar Youcef

机构信息

UMR6602 Institut Pascal (IP), Université Clermont Auvergne, SIGMA Clermont, Clermont-Ferrand, France.

出版信息

Front Robot AI. 2021 Feb 18;7:600387. doi: 10.3389/frobt.2020.600387. eCollection 2020.

Abstract

This paper presents a novel approach to implement hierarchical, dense and dynamic reconstruction of 3D objects based on the VDB (Variational Dynamic B + Trees) data structure for robotic applications. The scene reconstruction is done by the integration of depth-images using the Truncated Signed Distance Field (TSDF). The proposed reconstruction method is based on dynamic trees in order to provide similar reconstruction results to the current state-of-the-art methods (i.e., complete volumes, hashing voxels and hierarchical volumes) in terms of execution time but with a direct multi-level representation that remains real-time. This representation provides two major advantages: it is a hierarchical and unbounded space representation. The proposed method is optimally implemented to be used on a GPU architecture, exploiting the parallelism skills of this hardware. A series of experiments will be presented to prove the performance of this approach in a robot arm platform.

摘要

本文提出了一种基于VDB(变分动态B+树)数据结构的新颖方法,用于机器人应用中实现3D物体的分层、密集和动态重建。场景重建通过使用截断符号距离场(TSDF)对深度图像进行融合来完成。所提出的重建方法基于动态树,以便在执行时间方面提供与当前最先进方法(即完整体积、哈希体素和分层体积)相似的重建结果,但具有直接的多级表示且保持实时性。这种表示提供了两个主要优点:它是一种分层且无界的空间表示。所提出的方法经过优化,可在GPU架构上使用,利用该硬件的并行技能。将展示一系列实验,以证明该方法在机器人手臂平台上的性能。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d82/7935507/db8460de259e/frobt-07-600387-g001.jpg

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