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This paper proposes a unified vision-based manipulation framework using imagecontours of deformable/rigid objects. Instead of using human-defined cues, therobot automatically learns the features from processed vision data. Our methodsimultaneously generates -- from the same data -- both, visual features and theinteraction matrix that relates them to the robot control inputs. Extraction ofthe feature vector and control commands is done online and adaptively, withlittle data for initialization. The method allows the robot to manipulate anobject without knowing whether it is rigid or deformable. To validate ourapproach, we conduct numerical simulations and experiments with both deformableand rigid objects.

Vision-based Manipulation of Deformable and Rigid Objects Using Subspace Projections of 2D Contours