Mohamad Javad Aein

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The goal of this study is to provide an architecture for a generic definition of robot manipulation actions. We emphasize that the representation of actions presented here is “procedural”. Thus, we will define the structural elements of our action representations as execution protocols. To achieve this, manipulations are defined using three(More)
This paper presents an online learning scheme to train a Cellular Neural Network (CNN) which can be used to model multidimensional systems whose dynamics are governed by Partial Differential Equations (PDE). Most of the existing works in the literature employ fixed parameters which in turn implies an exact knowledge about the underlying PDE and/or its(More)
In this work we address the problem of finding replacements of missing objects that are needed for the execution of human-like manipulation tasks. This is a usual problem that is easily solved by humans provided their natural knowledge to find object substitutions: using a knife as a screwdriver or a book as a cutting board. On the other hand, in robotic(More)
Object recognition plays an important role in robotics, since objects/tools first have to be identified in the scene before they can be manipulated/used. The performance of object recognition largely depends on the training dataset. Usually such training sets are gathered manually by a human operator, a tedious procedure, which ultimately limits the size of(More)
This paper presents an online learning scheme to train a Cellular Neural Network (CNN) which can be used to model multidimensional systems whose dynamics are governed by Partial Differential Equations (PDE). Most of the previous work on CNN, employed fixed parameters or learning methods which need many iterations of an algorithm. There is a lack of fast,(More)
Human manipulation activity recognition is an important yet challenging task in robot imitation. In this paper, we introduce, for the first time, a novel method for semantic decomposition and recognition of continuous human manipulation activities by using on-line learned individual manipulation models. Solely based on the spatiotemporal interactions(More)
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