Bats are known for their highly capable biosonar systems which make them be able to navigate and forage in dense vegetation. Their biosonar system consists of one emitter (nose or mouth) and two receivers (ears). Some bat species, e.g. in the rhinolophid and hipposiderid families, have complicated pinna motion patterns. It has been shown that these pinna motion patterns fall into two distinct categories: rigid motions and non-rigid motions. In the current work, the pinna of Pratt's leaf-nosed bat (Hipposideros pratti) was used as a biological model system to understand how a sensor could benefit from variability. Hence, the variability in the rigid pinna motions and in the non-rigid pinna motions has been investigated by tracking a dense set of landmarks on the pinna surface with stereo vision. Axis-angle representations have shown that the rigid pinna motions exhibited a large continuous variation with rotation axes covering 180 degrees in azimuth and elevation. Distributions of clusters of the landmarks on the pinna surface have shown that the non-rigid pinna motions fall into at least two subgroups. Besides, the acoustic impact of the rigid pinna motions have been investigated using a biomimetic pinna. Normalized mutual information between the acoustic inputs with different rotation axes has shown that different rotation axes can provide at least 50% new sensory information. These results demonstrate that the variability in the pinna motions is an interesting concept for sensor, and how the bats approach that needs to be further investigated. / Master of Science / Sensors have been developed for a long time, and they can be used to detect the environments and then deliver the required sensing information. There are many different types of sensors, such as vision-based sensors (infrared camera and laser scanner) and sound-based sensors (sonar and radar). Ultrasonic transducers are one of the sound-based sensors, and they are more stable and reliable in environments where smoke or steam is present. Similar to human-made ultrasonic transducers, bats have developed highly capable biosonar systems that consist of one ultrasonic emitter (nose or mouth) and two ultrasonic receivers (ears), and these biosonar systems enable them to fly and hunt in cluttered environments. Some bats, e.g. rhinolophid and hipposiderid bats, have dynamic noseleaves (elaborate baffle shapes surrounding the nostrils) and pinna (outer ear), and these could enhance the sensing abilities of bats. Hence, the purpose of this thesis has been to investigate this variability to improve the human-made sensors by focusing on the dynamic pinna of the bats. It has been shown that bats have two distinct categories of pinna motions: rigid motions which change only the orientation of the pinna, and non-rigid motions which change also the shape of the pinna. However, the variability within the rigid and non-rigid pinna motions has received little attention. Therefore, the present work has investigated the variability in the rigid pinna motions and in the non-rigid pinna motions. Landmark points were placed on the pinna of certain bats and the pinna motions were tracked by high-speed video cameras. The rigid pinna motions exhibit a large continuous variation in where the pinna is orientated during rotation. Distributions of clusters of the landmarks on the pinna have shown that the non-rigid pinna motions fall into at least two subgroups. The acoustic impacts of the rigid pinna motions have been studied by a biomimetic pinna which reproduced the observed range of the rigid pinna motions. Ultrasonic signals mimicking the bats were emitted to be received by the biomimetic pinna. Based on these signals, it has been shown that different rotation axes and even small changes can provide over 50% new sensory information. These findings give engineers a potential way to improve the human-made sensors.

Many animal species are known for their unparalleled abilities to encode sensory information that supports fast, reliable action in complex environments, but the mechanisms remain often unclear. Through fast ear motions, bats can encode information on target direction into time-frequency Doppler signatures. These species were thought to be evolutionarily tuned to Doppler shifts generated by a prey's wing beat. Self-generated Doppler shifts from the bat's own flight motion were for the most part considered a nuisance that the bats compensate for. My findings indicate that these Doppler-based biosonar systems may be more complicated than previously thought because the animals can actively inject Doppler shifts into their input signals. The work in this dissertation presents a novel nonlinear principle for sensory information encoding in bats. Up to now, sound-direction finding has required either multiple signal frequencies or multiple pressure receivers. Inspired by bat species that add Doppler shifts to their biosonar echoes through fast ear motions, I present a source-direction finding paradigm based on a single frequency and a single pressure receiver. Non-rigid ear motions produce complex Doppler signatures that depend on source direction but are difficult to interpret. To demonstrate that deep learning can solve this problem, I have combined a soft-robotic microphone baffle that mimics a deforming bat ear with a CNN for regression. With this integrated cyber-physical setup, I have able to achieve a direction-finding accuracy of 1 degree based on a single baffle motion. / Doctor of Philosophy / Bats are well-known for their intricate biosonar system that allow the animals to navigate even the most complex natural environments. While the mechanism behind most of these abilities remains unknown, an interesting observation is that some bat species produce fast movements of their ears when actively exploring their surroundings. By moving their pinna, the bats create a time-variant reception characteristic and very little research has been directed at exploring the potential benefits of such behavior so far. One hypothesis is that the speed of the pinna motions modulates the received biosonar echoes with Doppler-shift patterns that could convey sensory information that is useful for navigation. This dissertation intends to explore this hypothetical dynamic sensing mechanism by building a soft-robotic biomimetic receiver to replicate the dynamics of the bat pinna. The experiments with this biomimetic pinna robot demonstrate that the non-rigid ear motions produce Doppler signatures that contain information about the direction of a sound source. However, these patterns are difficult to interpret because of their complexity. By combining the soft-robotic pinna with a convolutional neural network for processing the Doppler signatures in the time-frequency domain, I have been able to accurately estimate the source direction with an error margin of less than one degree. This working system, composed of a soft-robotic biomimetic ear integrated with a deep neural net, demonstrates that the use of Doppler signatures as a source of sensory information is a viable hypothesis for explaining the sensory skills of bats.