How do many active-sensing agents like echolocating bats move together and show collective movement in large groups? Each individual in the group is constantly emitting intense calls to detect their surroundings, while relying on echoes and other sounds to detect their environment. How do agents manage the cacophony of sounds, relevant and irrelevant - and what to do they to mitigate this potential sensory overload? Such acoustically based groups showing rapid movements are a frontier field for collective behaviours as such and present an exciting nexus from a basic and technological perspective. In this talk I will present my lab's multi-pronged approach at answering this inverse problem using a combination of swarm robotics, computer simulations and multi-sensor rigs in the field. The computational methods to process and analyse such experimental data itself do not currently exist in any form - which we are also driving through collaborations. Bringing together the fields of sensory biology, collective behaviour, swarm robotics, and computational methods development - I will discuss the challenges and advantages of such an approach.