7 June 2002 Pose estimation for autonomous robotic grasping
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Abstract
The development of anthropomorphic robots for simple autonomous operations such as grasping of tools requires algorithms for automatic recognition and pose estimation of the objects. Correlation-based pattern recognition offers a robust set of tools for pose-specific detection and identification of objects. This paper discusses a system-level approach to image understanding whereby a robot is provided with training data (in the form of a computer model and an associated matched filter set), is presented with a view of the target object, and is expected to indicate recognition and to calculate a six degree-of-freedom pose estimate for the object. The pose information would then be used to specify a grasping orientation for the robot's hand. Examples are given of a proof-of-concept demonstration of an approach for an anthropomorphic robot developed at the Johnson Space Center.
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Stanley E. Monroe, Stanley E. Monroe, John Michael Rollins, John Michael Rollins, Richard D. Juday, Richard D. Juday, "Pose estimation for autonomous robotic grasping", Proc. SPIE 4735, Hybrid Image and Signal Processing VIII, (7 June 2002); doi: 10.1117/12.470109; https://doi.org/10.1117/12.470109
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