In modern robotic field, many challenges have been appeared, especially in case of a multi-robot system that used to achieve tasks. The challenges are due to the complexity of the multi-robot system, which make the modeling of such system more difficult. The groups of animals in real world are an inspiration for modeling of a multi-individual system such as aggregation of Artemia. Therefore, in this paper, the multi-robot control system based on external stimuli such as light has been proposed, in which the feature of tracking Artemia to the light has been employed for this purpose. The mathematical model of the proposed design is derived and then Simulated by V-rep software. Several experiments are implemented in order to evaluate the proposed design, which is divided into two scenarios. The first scenario includes simulation of the system in situation of attraction of robot to fixed light spot, while the second scenario is the simulation of the system in the situation of the robots tracking of the movable light spot and formed different patterns like a straight-line, circular, and zigzag patterns. The results of experiments appeared that the mobile robot attraction to high-intensity light, in addition, the multi-robot system can be controlled by external stimuli. Finally, the performance of the proposed system has been analyzed.

Wireless sensor networks (WSNs) contain many sensor nodes, and this network is used for many applications such as military, medical, and others. Accurate data aggregation and routing are critical in hostile environments, where sensors' energy consumption must be carefully monitored. There is, nevertheless, a substantial probability of duplicate data due to ambient circumstances and shortdistance sensors. Large datasets include a variety of information, some of which is useful, while others are completely superfluous. This redundancy degrades performance in terms of computing cost and redundant transmission. Data aggregation, on the other hand, may eliminate redundant data in a network. In this paper new method called Kalman filter with Support vector machine (KF-SVM) is introduced to classify and data aggregate and get rid of noise in WSNs, which enhances network efficiency and extends its lifetime. Povzetek: V prispevku je opisana izvirna metoda za agregiranje podatkov v senzorskih omrežjih, ki dela na osnovi Kalmanovega filtra in SVM.

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