1 An efficient search algorithm is very crucial in robotic area, especially for exploration missions, where the target availability is unknown and the condition of the environment is highly unpredictable. In a very large environment, it is not sufficient to scan an area or volume by a single robot, multiple robots should be involved to perform the collective exploration. In this paper, we propose to combine bio-inspired search algorithm called Levy flight and artificial potential field method to perform an efficient searching algorithm for multi-robot applications. The main focus of this work is not only to prove the concept or to measure the efficiency of the algorithm by experiments, but also to develop an appropriate generic framework to be implemented both in simulation and on real robotic platforms. Several experiments, which compare different search algorithms, are also performed.

Energy supply is one of the most serious problems for micro-mechatronic devices. For collective systems, such as sensor networks or swarms of autonomous micro-robots, collective energy management is especially hard. This work describes a kinetic model of energy foraging and an application of bio-inspired harvesting behaviour to a real robot swarm. The heuristic strategy derived allows proper collective management of energy resources without using global knowledge and guarantees a good swarm efficiency. Despite the whole swarm having the same behavioural rules, some robots specialize in only a few foraging activities, whereas others are more universal in their behaviour. Such emergence of 'specialists' and 'generalists' is observed in animal groups and can indicate common behavioural principles underlying natural and artificial systems.

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Various organisms share certain basic rules for a searching behavior. We hypothesize that these rules may emerge from basic properties of nonlinear systems as a whole, rather then being evolved from a scratch gradually. In order to support this hypothesis, we have developed a virtual agent that consists of three simple nonlinear oscillators. These oscillators are driven by an internal noise, which results in phase transitions in their activity. External stimuli modify the activity via sensors and food consumption. The interaction among the activity of oscillators and external influences give rise to an emergence of searching rules that are similar to those shared by various organisms, thus favoring this hypothesis. The hypothesis can be verified further by investigating various types of nonlinear systems in different environments.

In humans, hemispheric language dominance is, to some degree, associated with handedness. Significant associations have been reported between several other lateralized functions. Much less is known about the organization of cerebral asymmetries in nonhuman species and, in particular, whether the presence of reversed asymmetry of one function is associated with a reversal of other lateralized functions or, instead, if cognitive functions lateralize independently. In this study, we compare four measures of sensory and motor laterality in the same individuals in a sample of goldbelly topminnows. A significant association was found between two measures of eye preference and two measures of motor laterality, but sensory and motor asymmetries were uncorrelated. We found interesting that individuals preferring to examine a predator with the right eye tended to use the left eye to look at a shoal mate and the reverse was true for fish that monitored predators with the left eye. This complementarity of functions could be adaptively advantageous for a small social fish, because it allows an individual to monitor the movements of its shoal mates with one eye as the other eye remains free to scan the surroundings for the presence of predators.