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Relative spatial pose estimation for autonomous grasping

Authors: Michael Magee;

Relative spatial pose estimation for autonomous grasping

Abstract

A technique for finding the relative spatial pose between a robotic end effector and a target object to be grasped without a priori knowledge of the spatial relationship between the camera and the robot is presented. The transformation between the coordinate system of the camera and the coordinate system of the robot is computed dynamically using knowledge about the location of the end effector relative to both the camera and the robot. A previously developed computer vision tech- nique is used to determine the pose of the end effector relative to the camera. The robot geometry and data from the robot controller is used to determine the pose of the end effector relative to the robot. The spatial transformation between the robot end effector and the target object is computed with respect to the robot's coordinate system. The algorithm was demonstrated using a five-degree-of-freedom robot and an RGB camera system. The camera can be dynamically positioned without con- cern for an assumed spatial relationship between the camera and robot, enabling optimization of the view of the object and the end effector. Further, the iterative nature of the grasping algorithm reduces the effects of camera calibration errors. © 1997 Society of Photo-Optical Instrumentation En- gineers. (S0091-3286(97)01612-7)

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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