Beyond the Baseline: 3D Reconstruction of Tiny Objects With Single Camera Stereo Robot

Autor: Daniele De Gregorio, Matteo Poggi, Pierluigi Zama Ramirez, Gianluca Palli, Stefano Mattoccia, Luigi Di Stefano
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: IEEE Access, Vol 9, Pp 119755-119765 (2021)
Druh dokumentu: article
ISSN: 2169-3536
DOI: 10.1109/ACCESS.2021.3108626
Popis: Self-aware robots rely on depth sensing to interact with the surrounding environment, e.g. to pursue object grasping. Yet, dealing with tiny items, often occurring in industrial robotics scenarios, may represent a challenge due to lack of sensors yielding sufficiently accurate depth measurements. Existing active sensors fail at measuring details of small objects (< 1cm) because of limitations in the working range, e.g. usually beyond 50 cm away, while off-the-shelf stereo cameras are not suited to close-range acquisitions due to the need for extremely short baselines. Therefore, we propose a framework designed for accurate depth sensing and particularly amenable to reconstruction of miniature objects. By leveraging on a single camera mounted in eye-on-hand configuration and the high repeatability of a robot, we acquire multiple images and process them through a stereo algorithm revised to fully exploit multiple vantage points. Using a novel dataset addressing performance evaluation in industrial applications, our Single camera Stereo Robot (SiSteR) delivers high accuracy even when dealing with miniature objects. We will provide a public dataset and an open-source implementation of our proposal to foster further development in this field.
Databáze: Directory of Open Access Journals