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Communication Dans Un Congrès Année : 2010

Crossing the Reality Gap in Evolutionary Robotics by Promoting Transferable Controllers

Résumé

The reality gap, that often makes controllers evolved in simulation inefficient once transferred onto the real system, remains a critical issue in Evolutionary Robotics (ER); it prevents ER application to real-world problems. We hypothesize that this gap mainly stems from a conflict between the efficiency of the solutions in simulation and their transferability from simulation to reality: best solutions in simulation often rely on bad simulated phenomena (e.g. the most dynamic ones). This hypothesis leads to a multi-objective formulation of ER in which two main objectives are optimized via a Pareto-based Multi-Objective Evolutionary Algorithm: (1) the fitness and (2) the transferability. To evaluate this second objective, a simulation-to-reality disparity value is approximated for each controller. The proposed method is applied to the evolution of walking controllers for a real 8-DOF quadrupedal robot. It successfully finds effi- cient and well-transferable controllers with only a few experiments in reality.
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Dates et versions

hal-00633927 , version 1 (19-10-2011)

Identifiants

  • HAL Id : hal-00633927 , version 1

Citer

Sylvain Koos, Jean-Baptiste Mouret, Stéphane Doncieux. Crossing the Reality Gap in Evolutionary Robotics by Promoting Transferable Controllers. Conference on Genetic and Evolutionary Computation, Jul 2010, United States. pp.119-126. ⟨hal-00633927⟩
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