Research by Nicole Abaid
Many species of bats fly together in groups that appear remarkably similar to other aerial social animals, like bird flocks and insect swarms. However, bats are unique among these examples of collective behavior in that they achieve their coordination using echolocation, which relies on self-generated acoustic signals interacting with the environment. By design, these signals and their echoes can be intercepted by other animals in the group, resulting in a unique coupling between sensing and communication. For example, this sensing modality could result in confusion between an individual’s own signal and that of its peers, yet bats in the wild and in laboratory experiments do not seem to suffer from this confusion for reasons that are not well understood.
Current work in the BIST center focuses on experimentally assessing information flow between bats flying in groups. Using techniques from dynamical systems, this work seeks to explore interactions between individual animals that may differ from patterns of information sharing in animal groups that rely primarily on passive sensing, such as vision. Experimental work focuses capturing these evolutionarily-refined behaviors from bat swarms in natural settings, such as caves. This research has the potential to uncover collective behaviors novel to systems with active sensing which may be implemented in similarly sensorized engineered applications.