Article of UCM Team on Motion Recognition Using a Transformer Model and LIDAR Sensor

Within framework of WP4, the UCM team of the project FAAI has published the paper “Playing Flappy Bird Based on Motion Recognition Using a Transformer Model and LIDAR Sensor” in Sensors MDPI.  The authors study a good practice using a transformer neural network which is employed in order to predict Q-values in a simulated environment using reinforcement learning techniques. The goal is to teach an agent to navigate and excel in the Flappy Bird game, which became a popular model for control in machine learning approaches. Unlike most top existing approaches that use the game’s rendered image as input, our main contribution lies in using sensory input from LIDAR, which is represented by the ray casting method.
Going forward, the authors aim to apply this approach in real-world scenarios.

The link to the paper is https://doi.org/10.3390/s24061905