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ECVision indexed and annotated bibliography of cognitive computer vision publications
This bibliography was created by Hilary Buxton and Benoit Gaillard, University of Sussex, as part of ECVision Specific Action 8-1
The complete text version of this BibTeX file is available here: ECVision_bibliography.bib


M. Salganicoff and G. Metta and A. Oddera and G. Sandini
A Vision-Based Learning Method for Pushing Manipulation

ABSTRACT

We describe an unsupervised on-line method for learning of manipulative actions that allows a robot to push an object connected to it with a rotational point contact to a desired point in image-space. By observing the results of its actions on the object's orientation in image-space, the system forms a predictive forward empirical model. This acquired model is used on-line for manipulation planning and control as it improves. Rather than explicitly inverting the forward model to achieve trajectory control, a stochastic action selection technique is used to select the most informative and promising actions, thereby integrating active perception and learning by combining on-line improvement, task directed exploration, and model exploitation. Simulation and experimental results of the approach are presented


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