Tool to pick objects out of a bin using qualitative-vision and part-reflectance properties

Marcello Ricotti

doi:10.1117/12.141788

11 March 1993 Tool to pick objects out of a bin using qualitative-vision and part-reflectance properties

Marcello Ricotti

Proceedings Volume 1964, Applications of Artificial Intelligence 1993: Machine Vision and Robotics; (1993) https://doi.org/10.1117/12.141788
Event: Optical Engineering and Photonics in Aerospace Sensing, 1993, Orlando, FL, United States

Abstract

A new approach to the quasi specular object picking task is described. Purposive and qualitative vision is used to detect the object to be picked. Surface reflectance properties and appropriate lighting directions are used to estimate the surface orientation. Extrinsic camera calibration parameters are used to compute the part attitude in a world reference system. A pneumatic gripper with proximity sensors on its extremities is used to effectively grasp the part. The acquisition sequence is driven by prior knowledge about the object to be grasped as well as by the reflectance properties of its surface. The purposive picking algorithm does not perform any 3-D reconstruction of the scene, but identifies the part to be picked as the part which is not occluded by any other part. Due to the purposive nature of the method no 3-D scene nor 3-D part modeling is required. Our method is characterized by having low sensitivity to image noise and being robust and applicable to a wide range of industrial plastic and metal objects whose bidirectional reflectance distribution function (BDRF) approximates an ideal specular reflector. Test results using a real framework with metallic hexagonal rods are described. Experiments with cylindrical, square, and generic polygon base rods are in process giving encouraging results.

Citation Download Citation

Marcello Ricotti "Tool to pick objects out of a bin using qualitative-vision and part-reflectance properties", Proc. SPIE 1964, Applications of Artificial Intelligence 1993: Machine Vision and Robotics, (11 March 1993); https://doi.org/10.1117/12.141788

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
10 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Image segmentation

3D modeling

Evolutionary algorithms

Cameras

Artificial intelligence

Image processing

Light sources and illumination

Show All Keywords

Keywords/Phrases

Search In:

Publication Years