Analyzing the complexity of bat flight to inspire the design of flapping-flight drones

Abstract

With their exceptionally maneuverable flapping flight, bats could serve as a model for enhancing the flight abilities for future drones. However, bat flight is extremely complex and there are many engineering restrictions that prevent a flapping-flight drone from replicating the many degrees of freedoms present in biology. Hence, to make design choices of which properties in a bats wing kinematics should be reproduced, the present research has evaluated two metrics from information and complexity theory to identify which regions of the bat flight apparatus are most complex and where coupling across features of the bat flight kinematics exists. The values were the complexity metric as a measure of variability and mutual information as a measure of coupling. Both measures were applied to ten experimentally obtained digital models of the flight kinematics in Ridley's leaf-nosed bats as well as the simulated kinematics of a flapping-flight drone inspired by the same bat type. The pilot results obtained indicate that both measures could be useful to discover which elements of flight kinematics should be looked into for understanding and reproducing the maneuvering flight of bats. However, a functional interpretation will require complementary, e.g., aerodynamic metrics.