Abstraction as a Tool to Bridge the Reality Gap in Evolutionary Robotics

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Automatically optimizing robotic behavior to solve complex tasks has been one of
the main, long-standing goals of Evolutionary Robotics (ER). When successful, this
approach will likely fundamentally change the rate of development and deployment
of robots in everyday life. Performing this optimization on real robots can be risky
and time consuming. As a result, much of the work in ER is done using simulations
which can operate many times faster than realtime. The only downside of this, is
that, due to the limited fidelity of the simulated environment, the optimized robotic
behavior is typically different when transferred to a robot in the real world. This
difference is referred to as the reality gap...