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Energy Aware Particle Swarm Optimization as search mechanism for aerial micro-robots

机译:能量感知粒子群优化算法作为空中微型机器人的搜索机制

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This paper presents the Energy Aware PSO (EAPSO) as a search mechanism for aerial micro-robots with limited energy capacity. The proposed model is an extension of the search concept of Particle Swarm Optimization (PSO) that additionally considers the energy levels of the individuals for an efficient movement. One major contribution of this paper is that the energy efficiency results from a multi-criteria decision making process performed by the individuals. The energy consumption model in EAPSO is adapted from a real hardware scenario and has been tested on three known landscapes which are very similar to search terrains by the aerial micro-robots. The results show that EAPSO can reduce the total energy consumption of the swarm with negligible degradation of the search results.
机译:本文介绍了能量感知PSO(EAPSO)作为能量有限的空中微型机器人的搜索机制。所提出的模型是粒子群优化(PSO)搜索概念的扩展,它另外考虑了个体的能量水平以进行有效运动。本文的一个主要贡献是,能源效率是由个人执行的多标准决策过程产生的。 EAPSO中的能耗模型是根据实际硬件场景改编而成,并已在三个已知的地形上进行了测试,这三个地形与空中微型机器人的搜索地形非常相似。结果表明,EAPSO可以减少群的总能耗,而搜索结果的降级可以忽略不计。

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