An experimental array setup to study the integration of biosonar and maneuvering flight in bats

Abstract

Understanding biosonar-based flight control in bats remains a challenge for fundamental bioacoustics and holds promise for engineered flight-control systems, especially for highly maneuverable drones. To accomplish this, detailed data on bat flight is required that captures the variability across flight situations, individuals, and species. Hence, a flight tunnel has been constructed that provides enough space for natural flight maneuvers. Reconstructing the detailed geometry of freely maneuvering bats requires capturing a flying bat from many different angles to ensure freedom from occlusions. Ideally, this would also be done without placing artificial markers on the bat. Hence, a flight tunnel has been instrumented with arrays of 50 high-speed video cameras and 28 ultrasonic microphones that were all integrated within a modular canvas setup. The optical properties of each camera have been determined from multiple images taken of a panel with a calibration grid seen from different orientations. The spatial relationship between the cameras was estimated based on a large set of images containing random points created with an LED. Reconstructing the 3D geometries of the bats from large numbers of high-speed video frames requires an automated method due to the problem's complexity. To this end, deep-learning methods are currently under development.