CORDIS Project
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REAL-RL focuses on developing autonomous robots that learn from experience to perform a variety of tasks. By utilizing a model-based approach, it aims to enhance data efficiency and enable robots to adapt their behavior in real-time, paving the way for versatile robotic applications in various domains.
REAL-RL proposes a path to autonomous robots that learn from experience.
By learning to solve new and challenging tasks and exploiting their specific capabilities, they could become ubiquitous assistants to humans in an uncountable number of tasks.
Current control strategies for robots are developed only for particular tasks and are not versatile.
To ensure their functioning, it is necessary to have highly accurate physical models that precisely match all the essential aspects of the real world.…
EBERHARD KARLS UNIVERSITAET TUEBINGEN
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