SIGGRAPH '94 Proceedings of the 21st annual conference on Computer graphics and interactive techniques
Evolution of Plastic Control Networks
Autonomous Robots
Noise and the Reality Gap: The Use of Simulation in Evolutionary Robotics
Proceedings of the Third European Conference on Advances in Artificial Life
Combining Simulation and Reality in Evolutionary Robotics
Journal of Intelligent and Robotic Systems
Evolving soft robotic locomotion in PhysX
Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers
Evolving mobile robots in simulated and real environments
Artificial Life
Exploring new horizons in evolutionary design of robots
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Nonlinear System Identification Using Coevolution of Models and Tests
IEEE Transactions on Evolutionary Computation
Evolving locomotion for a simulated 12-DOF quadruped robot
IPCAT'12 Proceedings of the 9th international conference on Information Processing in Cells and Tissues
Fast damage recovery in robotics with the T-resilience algorithm
International Journal of Robotics Research
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Methods for dealing with the problem of the "reality gap" in evolutionary robotics are described. The focus is on simulator tuning, in which simulator parameters are adjusted in order to more accurately model reality. We investigate sample selection, which is the method of choosing the robot controllers, evaluated in reality, that guide simulator tuning. Six strategies for sample selection are compared on a robot locomotion task. It is found that strategies that select samples that show high fitness in simulation greatly outperform those that do not. One such strategy, which selects the sample that is the expected fittest as well as the most informative (in the sense of producing the most disagreement between potential simulators), results in the creation of a nearly optimal simulator in the first iteration of the simulator tuning algorithm.