CapriDB - Capture, Print, Innovate: A Low-Cost Pipeline and Database for Reproducible Manipulation Research
This enables reproducible manipulation research for robotics by allowing anyone with a camera to create and control object properties like mass distribution and size, though it is incremental as it builds on existing tracking and 3D printing methods.
The paper tackles the problem of expensive and controlled 3D scanning setups for robotics manipulation research by introducing a low-cost pipeline that uses monocular or RGB-D camera images to generate 3D object models, which are then 3D printed and tracked, resulting in highly detailed mesh models that are difficult to distinguish from originals and an initial database of 40 textured and printable models.
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 enables anyone with a camera to scan, print and track complex objects for manipulation research. The proposed approach results in highly detailed mesh models whose 3D printed replicas are at times difficult to distinguish from the original. A key motivation for utilizing 3D printed objects is the ability to precisely control and vary object properties such as the mass distribution and size 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.