2016
Recurrent Neural Networks for fast and robust vibration-based ground classification on mobile robots
ICRA 2016
This paper investigates Recurrent Neural Networks (RNNs), particularly Dynamic Cortex Memories (DCMs), an extension of Long Short Term Memories (LSTMs) for classification of 14 different ground types based on vibration data. Also a simple regularization technique called Sequence Boundary Dropout (SB