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Helping robots learn using demonstrations | MIT CSAIL

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Machine learning can help robots learn new skills by finding patterns in data, but it can take a lot of time and examples for them to do something seemingly simple such as grasping. If we want robots to be effective teammates that can help increase our productivity, efficiency, and even quality of life, then we need them to continuously learn complex tasks reliably and quickly. What if we could give them a hand when they need it, so they could learn more effectively? This project explores a master-apprentice model of learning that combines self-supervision with learning by demonstration. A robot learns to grasp on its own by repeatedly trying to pick up a bottle. But if it can't find a good grasp using its current model, it asks a person for help. The person is supervising the robot in a virtual reality (VR) control room, and they can take control of the robot to provide grasping demonstrations. The robot learns from these demonstrations, and then continues learning on its own. This al

Helping robots learn using demonstrations | MIT CSAIL Skip to main content Project Helping robots learn using demonstrations Help robots learn faster by providing demonstrations when they need help Machine learning can help robots learn new skills by finding patterns in data, but it can take a lot of time and examples for them to do something seemingly simple such as grasping. If we want robots to be effective teammates that can help increase our productivity, efficiency, and even quality of life, then we need them to continuously learn complex tasks reliably and quickly. What if we could give

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