While foraging and commuting, echolocating bats navigate to salient places in their surroundings. They are able to do this relying only on echolocation. Currently, we have only a very limited idea about the kind of information these animals extract from the returning echoes to support navigation. Recent findings in both insect vision and the sensory ecology of bats suggest that their navigation ability is based on statistical descriptors of the environment. This project aims at immersing an artificial echolocator, the Chirocopter, i.e. an unmanned aerial vehicle (UAV) equipped with an emission and recording apparatus, in real environments, re-enacting the behaviour recorded from freely behaving bats. In this approach, this project is the first to collect an ecologically valid set of stimuli (echoes) as perceived by flying bats. The dataset collected using the Chirocopter allows testing the hypothesis that a statistical representation of the environment underlies the navigation abilities of bats. Final aim of the project is to develop a bio-inspired algorithm for echo based navigation to explain the navigation capabilities of bats.