Object recognition based on tactile form perception

In this paper a self organising map is proposed for object recognition based on tactile form perception. A robot hand with three fingers, with the same number of degrees of freedom as the human hand, is used for obtaining the required tactile measurements. Finger joint angles were recorded when the hand was grasping different objects, in three different orientations. A self organising map was used to categorise objects based on the measurements obtained using the hand. The proposed system learnt to recognise objects of different shape, as well as objects of the same shape but different size. To test the generalisation ability of the system, new objects (different from the training set) were applied and it was observed that the system learnt to categorise objects based on their shape and size. This paper also investigates the reliability of object recognition using tactile form perception with noisy measurements, the maximum number of different objects that can be recognised without significantly degrading the performance and the ability to recognise similar shaped objects with small differences in dimensions. Based on the test results presented, the system can recognise 89% of 25 different objects. This promising performance suggests that tactile form perception can be reliably used for object recognition in robotic applications.