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Stanford Bioengineers Encourage Virtual Competitors to Vie For a Different Kind of Athletic Title


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A virtual skeleton that has learned to walk from scratch, using only a machine-learning algorithm

At this moment, computer-generated skeletons are competing in a virtual race, running, hopping and jumping as far as they can before collapsing in an electronic heap.

Credit: crowdAI.org

Researchers at Stanford University have built precise models of how individual muscles and limbs move in response to neural control signals, and organized a contest to develop models of the brain's movement control systems.

Thus far, 63 teams have submitted 145 concepts to the competition, which is one of five contests developed for the 2017 Neural Information Processing Systems conference.

Each team is supplied with computer models of the human body and the world that body must navigate, including stairs and other surfaces. Teams also face internal challenges such as weak or unreliable muscles, and each team is evaluated based on how far its modeled human overcomes those obstacles in a fixed period.

The researchers hope some teams will surmount all the various virtual obstacles imposed on them, while a longer-term goal is not only helping children with degenerative diseases, but also aiding the design of better-calibrated devices to assist with walking or carrying loads.

From Stanford News
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Abstracts Copyright © 2017 Information Inc., Bethesda, Maryland, USA


 

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