Robotic Sensor-view Recognition with Neural Networks
نویسنده
چکیده
I present methods for using neural-networks to recognize sensor views from a laser range-finder for robotic navigation. First, I show that a simple back-propagation network can form a highly accurate recognizer when supervised training data is available. Then I investigate the use of the “Chorus of Prototypes” model for representing sensor views suitably for unsupervised exploration. Some problems with the model were found, and I discuss potential solutions.
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