Enhancing MARL for reality gap reduction

El treball consta de dues parts principals. La primera, la realització d'un algorisme d'inteligència artificial que permet a un agent virtual (2 braços robòtics fent servir el simulador Gazebo i el software de control ROS) aprendre a completar una tasca per si sol. La segona part consisteix en construir físicament els robots i implementar-hi el mateix algorisme alhora que s'intenta minimitzar l'error que posa la realitat.
El trabajo se compone de dos partes principales. La primera, la realización de un algoritmo de inteligencia artificial que permite a un agente virtual (en este caso 2 brazos robóticos simulados mediante Gazebo i el software de control ROS) aprender a completar una actividad por sí solo. La segunda parte consiste en construir físicamente los robots e implementar el mismo algoritmo a la vez que se intenta reducir el error que impone el medio real.
This research addresses some of the challenges concerning Multi-Agent Reinforcement Learning. Specifically, it focuses on reducing the reality gap in a MARL environment through the training of a Deep Reinforcement Learning policy. The study also aims to enhance the skills and knowledge learned during the bachelors’ degree in electronics engineering while contributing to the academic goal of bridging the sim-to-real-transfer issue. Simulation outcomes demonstrate successful learning by the agent while implementation falls short due to critical oversights in the early phases of the project concerning time management design. Personal goals, including the familiarization of several frameworks such as Gazebo, ROS 2 and Linux, as well as enhancing Python and C++ programming skills, are fully achieved. Despite challenges, resources developed while pursuing this project, such as the policy (DDPG), test files and other classes, are robust and reusable. Therefore, it is encouraged that future works in similar domains make use of them. In conclusion, the research provides valuable insights into the challenges of MARL implementation, highlighting the need for careful project management and offering reusable resources for future endeavours.
Outgoing