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Optimization of centipede robot body designs through evolutionary algorithms and multiple rough terrains simulation

Oleg Bulichev, Alexandr Klimchik, Nikolaos Mavridis

发表年份
2017
引用次数
5

摘要

Biomimetic centipede robots can be well-suited to a number of applications, including search-and-rescue around demolished rubble, logistics in rocky and hazardous areas, and more. The design space for such robots in quite large, with numerous open possibilities for body and leg shapes, configurations and numbers of components. On the other hand, realistic systems aim toward optimizing various performance measures, some of which can be directly calculated from the design parameters, while others require physical experimentation and simulation. In this paper, we present parametric models of centipede robots as well as rough terrains, and then we evaluate the performance of different robot designs across different terrains. We incrementally derive better designs through an appropriately crafted evolutionary algorithm. Promising results as well as insights are discussed. Finally, we provide a clear list of future steps and a forward-looking conclusion.

关键词

RobotTerrainComputer scienceEvolutionary algorithmParametric statisticsRubbleArtificial intelligenceAlgorithmSimulationEngineering

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