Object Recognition for Humanoid Robot using Tactile image processing and Artificial Neural Network

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Somchai Pohtongkam Jakkree Srinonchat


This paper presents an improvement recognition objects system, in the term of touching surface of objects, by using Artificial Neural Networks (ANNs). The experiment of this article is implemented and designed base on the robot hand for installs a sensor array on the robot hand. The sensor array is designed as 16X10 pixels. When the robot hand touches the object, the data is then organized into the image form for processing. This is to identify the characterize of object surface which different objects will provides a different images. This also depends on the force to touch objects. Then the Artificial Neural Networks technique is used to classify the objects. This system is tested with 10 different objects. The experiment results shown that it provides the accuracy approximately 93.2% based on average and standard deviation values.


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