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Reusing the tactile knowledge of some previously-explored objects helps ushumans to easily recognize the tactual properties of new objects. In thismaster thesis, we enable arobotic arm equipped with multi-modal artificialskin, like humans, to actively transfer the prior tactile exploratory actionexperiences when it learns the detailed physical properties of new objects.These prior tactile experiences are built when the robot applies the pressing,sliding and static contact movements on objects with different actionparameters and perceives the tactile feedbacks from multiple sensorymodalities. Our method was systematically evaluated by several experiments.Results show that the robot could consistently improve the discriminationaccuracy by over 10% when it exploited the prior tactile knowledge comparedwith using no transfer method, and 25% when it used only one training sample.The results also show that the proposed method was robust against transferringirrelevant prior tactile knowledge.

Leveraging Robotic Prior Tactile Exploratory Action Experiences For Learning New Objects's Physical Properties