TY - JOUR
T1 - Unknown object grasping using statistical pressure models
AU - Perrin, Doug
AU - Masoud, Osama
AU - Smith, Christopher E.
AU - Papanikolopoulos, Nikolaos P
PY - 2000/4
Y1 - 2000/4
N2 - 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.
AB - 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.
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U2 - 10.1109/ROBOT.2000.844739
DO - 10.1109/ROBOT.2000.844739
M3 - Article
AN - SCOPUS:0033727421
SN - 1050-4729
VL - 2
SP - 1054
EP - 1059
JO - Proceedings-IEEE International Conference on Robotics and Automation
JF - Proceedings-IEEE International Conference on Robotics and Automation
ER -
