  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.
