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Shadow is a proud winner of Awards.AI 2020 and the AIconics Award 2019 for Best Innovation in AI Hardware
Researchers have used neural networks to train our robot Hand in simulation using the trial-and-error principle (reinforcement learning).
The data is then transferred to our robot Hand so that it can perform the desired action in a real-life setting and in real-time.
Since our system has no prior information, it removes bias and enables researchers to explore the system freely for revolutionary results.
We’ve worked with OpenAI, founded by business tycoons, Elon Musk and Sam Altman to advance research within AI and machine learning using the Shadow Dexterous Hand.
HBP and Maastricht University successfully integrate and simulate the Shadow Hand on the HBP Neurorobotics Platform which connects a physics simulator to a variety of neural networks (or brains).
Google Brain used the Shadow Hand to learn how to manipulate multiple objects using just a few hours of real-world data.
“People are able to perform a wide range of dexterous manipulation tasks in a diverse set of environments, making the human hand a grounded source of inspiration for research into robotic manipulation”
“The Shadow Hand exhibits human-level dexterity which allows a research team at Maastricht University to study how the brain coordinates complex hand movements… By providing a highly realistic model of the human hand, the Shadow Hand allows neuroscientists to develop more realistic models around how the human brain works.”
Mario Senden, Assistant Professor
Faculty of Psychology and Neuroscience at Maastricht University
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