Terrain Identification with LSTM

This project focused on time-series classification using Deep Learning. I developed a Long Short-Term Memory (LSTM) neural network to classify terrain types (e.g., concrete, grass, gravel) based on raw gyroscope data collected from a mobile robot. The model was trained on a custom dataset and optimized to run efficiently, demonstrating the capability of recurrent neural networks to extract temporal features from inertial sensor data.