Title :
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
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;
Conference_Titel :
Robotics and Automation, 2000. Proceedings. ICRA '00. IEEE International Conference on
Conference_Location :
San Francisco, CA
Print_ISBN :
0-7803-5886-4
DOI :
10.1109/ROBOT.2000.844739
