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