Titlebook: New Horizons in Evolutionary Robotics; Extended Contributio Stéphane Doncieux,Nicolas Bredèche,Jean-Baptiste M Conference proceedings 2011

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Evolutionary Algorithms in the Design of Complex Robotic Systemsing into account in particular the variability of the environments in which they are intended to evolve constitutes challenges for the research in design. The needs in terms of rationality and efficiency in these new challenges for robotic engineering lead the development of systems to assist engine

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Evolutionary Algorithms to Analyse and Design a Controller for a Flapping Wings Aircraft and, on this basis, propose a controller for a complex robotics system: a flapping wings aircraft. A multi-objective optimization is performed to find the best parameters of sinusoidal wings kinematics. Multi-objective algorithms generate a set of trade-off solutions instead of a single solution. T

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On Applying Neuroevolutionary Methods to Complex Robotic Tasksevolve controllers for complex robotic tasks. The first problem is the large number of evaluations required to obtain a solution. We propose that this problem can be addressed by accelerating neuroevolutionary methods using a Kalman filter. The second problem is the difficulty of obtaining a desirab

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Evolutionary Design of a Robotic Manipulator for a Highly Constrained Environment lead to resort to evolutionary-aided design techniques. As the solution space is likely to be shaped strangely due to the particular environment, a special attention is paid to support the algorithm exploration and avoid negative impacts from the problem formulation, the fitness function or the eva

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A Multi-cellular Based Self-organizing Approach for Distributed Multi-Robot Systemsganizing multi-robot system for pattern formation. In our approach, multiple robots are able to self-organize themselves into various patterns driven by the dynamics of a gene regulatory network model. The pattern information is embedded into the gene regulation model, analog to the morphogen gradie

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Novelty-Based Multiobjectivizationbehaviors instead of the efficiency. However, abandoning the efficiency objective(s) may be too radical in many contexts. In this paper, a Pareto-based multi-objective evolutionary algorithmis employed to reconcile novelty search with objective-based optimization by following a multiobjectivization

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