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Abstract-In order to produce robots that are more capable of skilled manipulation tasks, they must learn meaningful knowledge of how objects behave to external stimulus. With this knowledge a robot can predict the outcome of an action, control the object to serve a particular purpose, and together with reasoning, create or modify robot plans. In this paper we 1) build a mathematical compact model for planar sliding motion of an object, 2) show how a robot acquires the parameters of such a model; then how this is used to 3) predict pushing actions; and 4) to move an object from any 1 position and orientation to another.

Abstract-When a robot wants to manipulate an object, it needs to know what action to execute to obtain the desired result. In most of the cases, the actions that can be applied to an object consist of exerting forces to it. If a robot is able to predict what will happen to an object when some force is applied to it, then it's possible to build a controller that solves the inverse problem of what force needs to be applied in order to get a desired result. To accomplish this, the first task is to build an object model and second to get the right parameters for it. The goals of this paper are 1) to demonstrate the use of an object model to predict outcomes of actions, and 2) to adapt this model to an specific object instance for a specific robot.