The project involves designing and evaluating energy-aware reinforcement learning (RL) algorithms for robotic systems. Emphasis is placed on integrating energy consumption metrics into RL frameworks and testing them in simulated robotic environments.
The study systematically compares different RL strategies, analysing their impact on robot behaviour, energy efficiency, and task performance.