Learning on real robots from their direct interaction with the environment
We present a new solution to achieve fast and continuous learning and adaptation processes on a real robot, even when the robot receives reinforcement from a human observer. The person does not need to have any kind of robotics knowledge, and will be able to provide the reward signal to the robot with a wireless joystick. Despite this highly-non-deterministic reinforcement, the robot is able to reach the desired behaviour in short periods of time.
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Publication: Congress
1624015018101
June 18, 2021
/research/publications/learning-on-real-robots-from-their-direct-interaction-with-the-environment
We present a new solution to achieve fast and continuous learning and adaptation processes on a real robot, even when the robot receives reinforcement from a human observer. The person does not need to have any kind of robotics knowledge, and will be able to provide the reward signal to the robot with a wireless joystick. Despite this highly-non-deterministic reinforcement, the robot is able to reach the desired behaviour in short periods of time. - R. Iglesias, M. A. Rodríguez, P. Quintía, C. V. Regueiro - 10.1007/978-3-642-32527-4_51
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