Unknown object grasping using statistical pressure models

Author

Perrin, Doug ; Masoud, Osama ; Smith, Christopher E. ; Papanikolopoulos, Nikolaos P.

Author_Institution

Dept. of Comput. Sci. & Eng., Minnesota Univ., Minneapolis, MN, USA

Volume

2

fYear

2000

fDate

2000

Firstpage

1054

Abstract

Grasping is one of the most fundamental and challenging tasks in robotics. Applications range from space missions (e.g., collection of rock samples) to industrial automation. In this work, we use a camera mounted on the end-effector of a manipulator to grasp an unknown object in the workspace. A novel deformable contour model is used to determine plausible grasp axes of the target object. Potential grasp point pairs are generated, ranked based upon measurements taken from the contour, and a vision-guided grasp of the object using the highest ranked grasp point pair is executed. Several experimental results are presented

Keywords

manipulators; robot vision; statistical analysis; camera; deformable contour model; end-effector; industrial automation; manipulator; plausible grasp axis determination; potential grasp point pairs; space missions; statistical pressure models; unknown object grasping; vision-guided grasp; Calibration; Computer science; Data mining; Deformable models; Manipulators; Orbital robotics; Robot vision systems; Robotics and automation; Service robots; Statistics;

fLanguage

English

Publisher

ieee

Conference_Titel

Robotics and Automation, 2000. Proceedings. ICRA '00. IEEE International Conference on

Conference_Location

San Francisco, CA

ISSN

1050-4729

Print_ISBN

0-7803-5886-4

Type

conf

DOI

10.1109/ROBOT.2000.844739

Filename

844739