Learning from Crickets: Artificial Hair-Sensor Array Developments

We have successfully developed biomimetic flowsensitive hair-sensor arrays taking inspiration from mechanosensory hairs of crickets. Our current generation of sensors achieves sub mm/s threshold air-flow sensitivity for single hairs operating in a bandwidth of a few hundred Hz and is the result of a few iterations in which the natural system (i.e. crickets filiform hair based mechano-sensors) have shown ample guidance to optimization. Important clues with respect to mechanical design, aerodynamics, viscous coupling effects and canopy based signal processing have been used during the course of our research. It is only by consideration of all these effects that we now may start thinking of systems performing a “flow-camera” function as found in nature in a variety of species

Bio-inspired motion detection in an FPGA-based smart camera module

Köhler T, Roechter F, Lindemann JP, Möller R. Bio-inspired motion detection in an FPGA-based smart camera module. Bioinspiration & Biomimetics. 2009;4(1):015008.Flying insects, despite their relatively coarse vision and tiny nervous system, are capable of carrying out elegant and fast aerial manoeuvres. Studies of the fly visual system have shown that this is accomplished by the integration of signals from a large number of elementary motion detectors (EMDs) in just a few global flow detector cells. We developed an FPGA-based smart camera module with more than 10000 single EMDs, which is closely modelled after insect motion-detection circuits with respect to overall architecture, resolution and inter-receptor spacing. Input to the EMD array is provided by a CMOS camera with a high frame rate. Designed as an adaptable solution for different engineering applications and as a testbed for biological models, the EMD detector type and parameters such as the EMD time constants, the motion-detection directions and the angle between correlated receptors are reconfigurable online. This allows a flexible and simultaneous detection of complex motion fields such as translation, rotation and looming, such that various tasks, e. g., obstacle avoidance, height/distance control or speed regulation can be performed by the same compact device

Tuning flow asymmetry with bio-inspired soft leaflets

In Nature, liquids often circulate in channels textured with leaflets, cilia or porous walls that deform with the flow. These soft structures are optimized to passively control flows and inspire the design of novel microfluidic and soft robotic devices. Yet so far the relationship between the geometry of the soft structures and the properties of the flow remains poorly understood. Here, taking inspiration from the lymphatic system, we devise millimetric scale fluidic channels with asymmetric soft leaflets that passively increase (reduce) the channel resistance for forward (backward) flows. Combining experiments, numerics and analytical theory, we show that tuning the geometry of the leaflets controls the flow properties of the channel through an interplay between asymmetry and nonlinearity. In particular, we find the conditions for which flow asymmetry is maximal. Our results open the way to a better characterization of biological leaflet malformations and to more accurate control of flow orientation and pumping mechanisms for microfluidics and soft robotic systems

Computational Approaches to Explainable Artificial Intelligence:Advances in Theory, Applications and Trends

Deep Learning (DL), a groundbreaking branch of Machine Learning (ML), has emerged as a driving force in both theoretical and applied Artificial Intelligence (AI). DL algorithms, rooted in complex and non-linear artificial neural systems, excel at extracting high-level features from data. DL has demonstrated human-level performance in real-world tasks, including clinical diagnostics, and has unlocked solutions to previously intractable problems in virtual agent design, robotics, genomics, neuroimaging, computer vision, and industrial automation. In this paper, the most relevant advances from the last few years in Artificial Intelligence (AI) and several applications to neuroscience, neuroimaging, computer vision, and robotics are presented, reviewed and discussed. In this way, we summarize the state-of-the-art in AI methods, models and applications within a collection of works presented at the 9 International Conference on the Interplay between Natural and Artificial Computation (IWINAC). The works presented in this paper are excellent examples of new scientific discoveries made in laboratories that have successfully transitioned to real-life applications

An experimental study of the elastic properties of dragonfly-like flapping wings for use in Biomimetic Micro Air Vehicles (BMAV)

This article studies the elastic properties of several biomimetic micro air vehicle (BMAV) wings that are based on a dragonfly wing. BMAVs are a new class of unmanned micro-sized air vehicles that mimic the flapping wing motion of flying biological organisms (e.g., insects, birds, and bats). Three structurally identical wings were fabricated using different materials: acrylonitrile butadiene styrene (ABS), polylactic acid (PLA), and acrylic. Simplified wing frame structures were fabricated from these materials and then a nanocomposite film was adhered to them which mimics the membrane of an actual dragonfly. These wings were then attached to an electromagnetic actuator and passively flapped at frequencies of 10–250 Hz. A three-dimensional high frame rate imaging system was used to capture the flapping motions of these wings at a resolution of 320 pixels × 240 pixels and 35000 frames per second. The maximum bending angle, maximum wing tip deflection, maximum wing tip twist angle, and wing tip twist speed of each wing were measured and compared to each other and the actual dragonfly wing. The results show that the ABS wing has considerable flexibility in the chordwise direction, whereas the PLA and acrylic wings show better conformity to an actual dragonfly wing in the spanwise direction. Past studies have shown that the aerodynamic performance of a BMAV flapping wing is enhanced if its chordwise flexibility is increased and its spanwise flexibility is reduced. Therefore, the ABS wing (fabricated using a 3D printer) shows the most promising results for future applications

Comparison of experiments on bio-inspired hover kinematics with the unsteady vortex model and CFD

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/106510/1/AIAA2013-66.pd

Validation of a Monte Carlo platform for the optical modelling of pulse oximetry

A custom Monte Carlo (MC) platform has been established to generate opto-physiological models of mechanisms in pulse oximetry. The current research is an exploration of the process of empirically validating such a platform. With the growing availability and accuracy of tissue optical properties in literatures, MC simulation of light-tissue interaction is providing increasingly valuable information for optical bio-monitoring research. However, the extent of the validity of results from such simulations depends heavily on its agreement with empirical data. The use of images captured from a CMOS camera for the construction of intensity distributions of light transmitted through the human finger has been investigated to compare with corresponding distributions produced in the MC simulations