Algorithms for the Analysis and Synthesis of a Bio-inspired Swarm Robotic System
Algorithms for the Analysis and Synthesis of a Bio-inspired Swarm Robotic System
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仿生群体机器人系统的分析和综合算法
DOI：
10.1007/978-3-540-71541-2_5
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发表时间：
2006
期刊：
影响因子：
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通讯作者：
S. Pratt
中科院分区：
文献类型：
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作者：
S. Berman;Á. Halász;Vijay R. Kumar;S. Pratt
我们提出了一种使用宏观连续模型来表征，分析和综合群体行为的方法，该模型代表群体作为连续体和宏观离散模型，列举了单个药物。我们的方法应用于蚂蚁狩猎的动态模型，这是一个分散的过程，其中殖民地试图移民到几种替代方案中的最佳地点。该模型是混合的，因为在此过程中，菌落在不同的行为或模式之间切换。使用[1]中的模型，我们研究了使用锥形过度毒性（MARCO）[2]的算法，研究了现场种群增长与初始系统状态的关系。然后，我们得出了尊重连续级别全局行为规范的代理的微观杂种动力学模型。我们的多级模拟表明，我们从宏观描述中产生了严格正确的微观模型。
We present a methodology for characterizing, analyzing, and synthesizing swarm behaviors using both a macroscopic continuous model that represents a swarm as a continuum and a macroscopic discrete model that enumerates individual agents. Our methodology is applied to a dynamical model of ant house hunting, a decentralized process in which a colony attempts to emigrate to the best site among several alternatives. The model is hybrid because the colony switches between different sets of behaviors, or modes, during this process. Using the model in [1], we investigate the relation of site population growth to initial system state with an algorithm called Multi-Affine Reachability analysis using Conical Overapproximations (Marco) [2]. We then derive a microscopic hybrid dynamical model of an agent that respects the specifications of the global behavior at the continuous level. Our multi-level simulations demonstrate that we have produced a rigorously correct microscopic model from the macroscopic descriptions.