Aggregation in Swarm Robotic Systems: Evolution and Probabilistic Control
Aggregation in Swarm Robotic Systems: Evolution and Probabilistic Control
复制标题
群体机器人系统中的聚合：进化和概率控制
DOI：
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发表时间：
2007
期刊：
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通讯作者：
E. Sahin
中科院分区：
文献类型：
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作者：
Onur Soysal;E. Bahçeci;E. Sahin
在本研究中，我们探讨了群体机器人系统中两种聚合行为的方法：进化方法和概率控制。第一部分以聚集行为为例，系统研究了不同参数设置下感知器控制器的聚集行为性能和可扩展性。使用一组计算机并行运行模拟，进行了四个实验，改变了一些参数。经验法则的推导，可以指导使用进化的方法来产生其他群体机器人的行为。第二部分对群体机器人系统中的概率聚合策略进行了系统的分析。提出了一种由避障、接近、击退和等待四种基本行为组合而成的通用聚合行为。后三种基本行为使用三态有限状态机进行组合，并在它们之间进行两次概率转换。两种不同的指标被用来比较策略的表现。通过系统实验，研究了以这两个指标衡量的聚合性能随转移概率、模拟步数和竞技场大小的变化规律。然后我们讨论这两种方法的聚合问题。
In this study we investigate two approachees for aggregation behavior in swarm robotics systems: Evolutionary methods and probabilistic control. In first part, aggregation behavior is chosen as a case, where performance and scalability of aggregation behaviors of perceptron controllers that are evolved for a simulated swarm robotic system are systematically studied with different parameter settings. Using a cluster of computers to run simulations in parallel, four experiments are conducted varying some of the parameters. Rules of thumb are derived, which can be of guidance to the use of evolutionary methods to generate other swarm robotic behaviors as well. In the second part a systematic analysis of probabilistic aggregation strategies in swarm robotic systems is presented. A generic aggregation behavior is proposed as a combination of four basic behaviors: obstacle avoidance, approach, repel, and wait. The latter three basic behaviors are combined using a three-state finite state machine with two probabilistic transitions among them. Two different metrics were used to compare performance of strategies. Through systematic experiments, how the aggregation performance, as measured by these two metrics, change 1) with transition probabilities, 2) with number of simulation steps, and 3) with arena size, is studied. We then discuss these two approaches for the aggregation problem.