This paper aims to use a fleet of mobile robots, each embedding a camera, to optimize the observation of a human dynamic scene. The scene is defined as a sequence of activities, performed by a person in a same place. Mobile robots have to cooperate to find a spatial configuration around the scene that maximizes the joint observation of the human pose skeleton. It is assumed that the robots can communicate but have no map of the environment and no external localisation. This paper presents a concentric navigation topology allowing to keep easily each robot camera towards the scene. This topology is combined with an incremental mapping of the environment in order to limit the complexity of the exploration state space. We also introduce the marginal contribution of each robot observation, to facilitate stability in the search, while the exploration is guided by a meta-heuristics. We developped a simulator that uses skeleton data from real human pose captures. It allows to compare the variants of the approach and to show its features such as adaptation to the dynamic of the scene and robustness to the noise in the observations.