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Using data retrieved from the Puppy II robot at the University of Zurich (UZH), we show that machine learning techniques with non-linearities and fading memory are effective for terrain classification, both supervised and unsupervised, even with a limited selection of input sensors. The results indicate that most information for terrain classification is found in the combination of tactile sensors...
Dogs are capable of showing rich motor skills in complex environments. No such capabilities have yet been seen in quadruped robots. In this work we present the design and realization of a biologically inspired quadruped robot based on a real dogs' anatomy. This dog, referred to as the Reservoir Dog, is capable of autonomously showing multiple gaits such as walk, which require active retraction of...
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