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

IEEE Access

Stefano Mattoccia¹  Pierluigi Zama Ramirez¹  Luigi Di Stefano²  Gianluca Palli³  Matteo Poggi³  Daniele De Gregorio⁴ 

[1] degli Studi di Bologna, Bologna, Italy;DEI, Universit&x00E0;DISI, Universit&x00E0;EYECAN.ai S.r.l, Bologna, Italy;

关键词: Intelligent robots;    robot learning;    robot vision systems;   

DOI  :  10.1109/ACCESS.2021.3108626

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown