By Stéphane Doncieux, Nicolas Bredeche, Jean-Baptiste Mouret
Evolutionary Algorithms (EAs) now supply mature optimization instruments that experience effectively been utilized to many difficulties, from designing antennas to accomplish robots, and supplied many human-competitive effects. In robotics, the mixing of EAs in the engineer’s toolbox made large development within the final two decades and proposes new the way to handle hard difficulties in a variety of setups: modular robotics, swarm robotics, robotics with non-conventional mechanics (e.g. excessive redundancy, dynamic movement, multi-modality), etc.
This booklet takes its roots within the workshop on "New Horizons in Evolutionary layout of Robots" that introduced jointly researchers from computing device technology and Robotics throughout the IEEE/RSJ foreign convention on clever Robots and structures (IROS-2009) in Saint Louis (USA). This ebook positive aspects prolonged contributions from the workshop, hence delivering a variety of examples of present difficulties and purposes, with a distinct emphasis at the hyperlink among laptop technology and Robotics. It additionally presents a finished and updated advent to Evolutionary Robotics after two decades of maturation in addition to recommendations and issues from numerous significant actors within the field.
This ebook bargains a complete advent to the present developments and demanding situations in Evolutionary Robotics for the subsequent decade.
Read Online or Download New Horizons in Evolutionary Robotics: Extended Contributions from the 2009 EvoDeRob Workshop PDF
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Additional resources for New Horizons in Evolutionary Robotics: Extended Contributions from the 2009 EvoDeRob Workshop
Once structures with high fitness were found, the existing structures in the population were re-grown at ‘high resolution’: more, smaller spheres were allowed for construction. An evolved low- and high-dimensional structure are shown in Fig. 2. 2 a The ‘What’, ‘How’ and the ‘Why’ of Evolutionary Robotics 33 b Fig. 2 Gradually Increasing Morphological Complexity. a: A structure evolved for maximum displacement when dropped. a: The same structure, but regrown at higher resolution. Several runs in which low-resolution structures were initially evolved and then further evolved at higher resolution were performed, and compared against a set of control runs in which structures were evolved at high resolution throughout.
Evolutionary computation 9(2), 159–195 (2001) 45. : Morpho-Functional Machines: The New Species: Designing Embodied Intelligence. Springer, Heidelberg (2003) 46. : Memory-enhanced evolutionary robotics. In: IEEE Congress on Evolutionary Computation (2009) 47. : Reverse-engineering of Artificially Evolved Controllers for Swarms of Robots. In: IEEE Congress on Evolutionary Computation (2009) 48. : Adaptation in natural and artificial systems: an introductory analysis with applications to biology, control, and artificial intelligence.
243–262 (2007) 22. : Evolutionary Algorithms to Analyse and Design a Controller for a Flapping Wings Aircraft. In: New Horizons in Evolutionary Robotics: PostProceedings of the 2009 EvoDeRob Workshop. Springer, Heidelberg (2010) 23. : Behavioral diversity measures for evolutionary robotics. In: IEEE Congress on Evolutionary Computation, CEC 2010 (to appear, 2010) 24. : Embodied, on-line, on-board evolution for autonomous robotics. , Kernbach, S. ) Symbiotic Multi-Robot Organisms: Reliability, Adaptability, Evolution, Cognitive Systems Monographs, vol.
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