A3C for drone autonomous driving using Airsim
- David Villota 1
- Montserrat Gil-Martínez 1
- Javier Rico Azagra 1
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1
Universidad de La Rioja
info
Editorial: Universitat Jaume I ; Servizo de Publicacións ; Universidade da Coruña ; Comité Español de Automática
ISBN: 978-84-9749-804-3
Año de publicación: 2021
Páginas: 203-209
Congreso: Jornadas de Automática (42. 2021. Castellón)
Tipo: Aportación congreso
Resumen
In this work, we apply artificial intelligence to guide a drone to a certain point autonomously. Unreal engine creates a virtual environment where the drone can fly, and the algorithm is trained simulating the drone dynamics thanks to Airsim plugin. The implemented algorithm is Asynchronous Actor-Critic Advantage (A3C), which trains a neural network with less computing resources than standard reinforcement learning algorithms that normally needs costly GPUs. To prove these advantages, several experiments are run using a different number of parallel simulations (threads). The drone should reach a point randomly generated each episode. The reward, the value and the advantage function are used to evaluate the performance. As expected, these experiments show that a higher number of threads helps the leaning process improve and become more stable. These learning results are of interest to optimize the computing resources in future applications.