A Database for Reproducible Manipulation Research: CapriDB - Capture, Print, Innovate

Artikel i vetenskaplig tidskrift, 2017

We present a novel approach and database which combines the inexpensive generation of 3D object models via monocular or RGB-D camera images with 3D printing and a state of the art object tracking algorithm. Unlike recent efforts towards the creation of 3D object databases for robotics, our approach does not require expensive and controlled 3D scanning setups and aims to enable anyone with a camera to scan, print and track complex objects for manipulation research. The proposed approach results in detailed textured mesh models whose 3D printed replicas provide close approximations of the originals. A key motivation for utilizing 3D printed objects is the ability to precisely control and vary object properties such as the size, material properties and mass distribution in the 3D printing process to obtain reproducible conditions for robotic manipulation research. We present CapriDB – an extensible database resulting from this approach containing initially 40 textured and 3D printable mesh models together with tracking features to facilitate the adoption of the proposed approach.