A new twist on gyroscopic sensing: body rotations lead to torsion in flapping, flexing insect wings

A Modular Soft Sensing Skin for Fast Measurement of Wing Deformation in Small Unmanned Aerial Vehicles

Insects, bats, and small birds show outstanding flight performance even under complex atmospheric conditions, which is partially due to the ability of these natural fliers to sense and react to disturbances quickly. These biological systems often use large numbers of sensors arrayed across their bodies to detect disturbances, but previous efforts to use large arrays of sensors in engineered fliers have typically resulted in slow responses due to the need to scan and process data from the large number of sensors. To address the challenges of capturing disturbances in a large sensing array with low latency, this work proposes and demonstrates a modular soft sensing system to quickly detect disturbances in small unmanned aerial vehicles. A large array of soft strain sensors with high sensing resolution covers the entire wingspan, providing rich information on wing deformation. Owing to the modular design, decentralized computation enables the sensing system to efficiently manage sensor data, resulting in sufficiently fast sampling to capture wing dynamics while all 32 sensors embedded in the modular soft sensing skin are used. This hardware architecture also results in significantly reduced noise in the sensing system, leading to a high signal-to-noise ratio. These methods can ultimately enable fast and reliable control of both soft and rigid robotic systems using large arrays of soft sensors.

Evolution, types, and distribution of flight control devices on wings and elytra in bark beetles

Gaining the ability to fly actively was a ground-breaking moment in insect evolution, providing an unprecedented advantage over other arthropods. Nevertheless, active flight was a costly innovation, requiring the development of wings and flight muscles, the provision of sufficient energetic resources, and a complex flight control system. Although wings, flight muscles, and the energetic budget of insects have been intensively studied in the last decades, almost nothing is known regarding the flight-control devices of many crucial insect groups, especially beetles (Coleoptera). Here, we conducted a phylogenetic-informed analysis of flight-related mechanosensors in 28 species of bark beetles (Curculionidae: Scolytinae, Platypodinae), an economically and ecologically important group of insects characterized by striking differences in dispersal abilities. The results indicated that beetle flight apparatus is equipped with different functional types of mechanosensors, including strain- and flow-encoding sensilla. We found a strong effect of allometry on the number of mechanosensors, while no effect of relative wing size (a proxy of flight investment) was identified. Our study constitutes the first step to understanding the drivers and constraints of the evolution of flight-control devices in Coleoptera, including bark beetles. More research, including a quantitative neuroanatomical analysis of beetle wings, should be conducted in the future.

Intraspecific Variation in the Placement of Campaniform Sensilla on the Wings of the Hawkmoth Manduca Sexta

Flight control requires active sensory feedback, and insects have many sensors that help them estimate their current locomotor state, including campaniform sensilla (CS), which are mechanoreceptors that sense strain resulting from deformation of the cuticle. CS on the wing detect bending and torsional forces encountered during flight, providing input to the flight feedback control system. During flight, wings experience complex spatio-temporal strain patterns. Because CS detect only local strain, their placement on the wing is presumably critical for determining the overall representation of wing deformation; however, how these sensilla are distributed across wings is largely unknown. Here, we test the hypothesis that CS are found in stereotyped locations across individuals of Manduca sexta, a hawkmoth. We found that although CS are consistently found on the same veins or in the same regions of the wings, their total number and distribution can vary extensively. This suggests that there is some robustness to variation in sensory feedback in the insect flight control system. The regions where CS are consistently found provide clues to their functional roles, although some patterns might be reflective of developmental processes. Collectively, our results on intraspecific variation in CS placement on insect wings will help reshape our thinking on the utility of mechanosensory feedback for insect flight control and guide further experimental and comparative studies.

Intraspecific variation in the placement of campaniform sensilla on the wings of the hawkmoth Manduca sexta

Flight control requires active sensory feedback, and insects have many sensors that help them estimate their current locomotor state, including campaniform sensilla, which are mechanoreceptors that sense strain resulting from deformation of the cuticle. Campaniform sensilla on the wing detect bending and torsional forces encountered during flight, providing input to the flight feedback control system. During flight, wings experience complex spatio-temporal strain patterns. Because campaniform sensilla detect only local strain, their placement on the wing is presumably critical for determining the overall representation of wing deformation; however, how these sensilla are distributed across wings is largely unknown. Here, we test the hypothesis that campaniform sensilla are found in stereotyped locations across individuals of Manduca sexta, a hawkmoth. We found that although campaniform sensilla are consistently found on the same veins or in the same regions of the wings, their total number and distribution can vary extensively. This suggests that there is some robustness to variation in sensory feedback in the insect flight control system. The regions where campaniform sensilla are consistently found provide clues to their functional roles, although some patterns might be reflective of developmental processes. Collectively, our results on intraspecific variation in campaniform sensilla placement on insect wings will help reshape our thinking on the utility of mechanosensory feedback for insect flight control and guide further experimental and comparative studies.

Nonuniform structural properties of wings confer sensing advantages

Sensory feedback is essential to both animals and robotic systems for achieving coordinated, precise movements. Mechanosensory feedback, which provides information about body deformation, depends not only on the properties of sensors but also on the structure in which they are embedded. In insects, wing structure plays a particularly important role in flapping flight: in addition to generating aerodynamic forces, wings provide mechanosensory feedback necessary for guiding flight while undergoing dramatic deformations during each wingbeat. However, the role that wing structure plays in determining mechanosensory information is relatively unexplored. Insect wings exhibit characteristic stiffness gradients and are subject to both aerodynamic and structural damping. Here we examine how both of these properties impact sensory performance, using finite element analysis combined with sensor placement optimization approaches. We show that wings with nonuniform stiffness exhibit several advantages over uniform stiffness wings, resulting in higher accuracy of rotation detection and lower sensitivity to the placement of sensors on the wing. Moreover, we show that higher damping generally improves the accuracy with which body rotations can be detected. These results contribute to our understanding of the evolution of the nonuniform stiffness patterns in insect wings, as well as suggest design principles for robotic systems.

A gyroscope-free visual-inertial flight control and wind sensing system for 10-mg robots

Tiny “gnat robots,” weighing just a few milligrams, were first conjectured in the 1980s. How to stabilize one if it were to hover like a small insect has not been answered. Challenges include the requirement that sensors be both low mass and high bandwidth and that silicon-micromachined rate gyroscopes are too heavy. The smallest robot to perform controlled hovering uses a sensor suite weighing hundreds of milligrams. Here, we demonstrate that an accelerometer represents perhaps the most direct way to stabilize flight while satisfying the extreme size, speed, weight, and power constraints of a flying robot even as it scales down to just a few milligrams. As aircraft scale reduces, scaling physics dictates that the ratio of aerodynamic drag to mass increases. This results in reduced noise in an accelerometer’s airspeed measurement. We show through simulation and experiment on a 30-gram robot that a 2-milligram off-the-shelf accelerometer is able in principle to stabilize a 10-milligram robot despite high noise in the sensor itself. Inspired by wind-vision sensory fusion in the flight controller of the fruit fly Drosophila melanogaster , we then added a tiny camera and efficient, fly-inspired autocorrelation-based visual processing to allow the robot to estimate and reject wind as well as control its attitude and flight velocity using a Kalman filter. Our biology-inspired approach, validated on a small flying helicopter, has a wind gust response comparable to the fruit fly and is small and efficient enough for a 10-milligram flying vehicle (weighing less than a grain of rice).

Accommodating unobservability to control flight attitude with optic flow

Attitude control is an essential flight capability. Whereas flying robots commonly rely on accelerometers¹ for estimating attitude, flying insects lack an unambiguous sense of gravity^2,3. Despite the established role of several sense organs in attitude stabilization^3-5, the dependence of flying insects on an internal gravity direction estimate remains unclear. Here we show how attitude can be extracted from optic flow when combined with a motion model that relates attitude to acceleration direction. Although there are conditions such as hover in which the attitude is unobservable, we prove that the ensuing control system is still stable, continuously moving into and out of these conditions. Flying robot experiments confirm that accommodating unobservability in this manner leads to stable, but slightly oscillatory, attitude control. Moreover, experiments with a bio-inspired flapping-wing robot show that residual, high-frequency attitude oscillations from flapping motion improve observability. The presented approach holds a promise for robotics, with accelerometer-less autopilots paving the road for insect-scale autonomous flying robots⁶. Finally, it forms a hypothesis on insect attitude estimation and control, with the potential to provide further insight into known biological phenomena^5,7,8 and to generate new predictions such as reduced head and body attitude variance at higher flight speeds⁹.

Spatial distribution of campaniform sensilla mechanosensors on wings: form, function, and phylogeny

Insect wings serve two crucial functions in flight: propulsion and sensing. During flapping flight, complex spatiotemporal patterns of strain on the wing reflect mechanics, kinematics, and external perturbations; sensing wing deformation provides feedback necessary for flight control. Campaniform sensilla distributed across the wing transduce local strain fluctuations into neural signals, so their placement on the wing determines sensory information available to the insect. Thus, understanding the significance of these sensor locations will also reveal how sensing and wing movement are coupled. Here, we identify trends in wing campaniform sensilla placement across flying insects from the literature. We then discuss how these patterns can influence sensory encoding by wing mechanosensors. Finally, we propose combining a comparative approach on model insect clades with computational modeling, leveraging the spectacular natural diversity in wings to uncover biological principles of mechanosensory feedback in flight control.

Wing structure and neural encoding jointly determine sensing strategies in insect flight

Animals rely on sensory feedback to generate accurate, reliable movements. In many flying insects, strain-sensitive neurons on the wings provide rapid feedback that is critical for stable flight control. While the impacts of wing structure on aerodynamic performance have been widely studied, the impacts of wing structure on sensing are largely unexplored. In this paper, we show how the structural properties of the wing and encoding by mechanosensory neurons interact to jointly determine optimal sensing strategies and performance. Specifically, we examine how neural sensors can be placed effectively on a flapping wing to detect body rotation about different axes, using a computational wing model with varying flexural stiffness. A small set of mechanosensors, conveying strain information at key locations with a single action potential per wingbeat, enable accurate detection of body rotation. Optimal sensor locations are concentrated at either the wing base or the wing tip, and they transition sharply as a function of both wing stiffness and neural threshold. Moreover, the sensing strategy and performance is robust to both external disturbances and sensor loss. Typically, only five sensors are needed to achieve near-peak accuracy, with a single sensor often providing accuracy well above chance. Our results show that small-amplitude, dynamic signals can be extracted efficiently with spatially and temporally sparse sensors in the context of flight. The demonstrated interaction of wing structure and neural encoding properties points to the importance of understanding each in the context of their joint evolution.

In addition to generating forces for flight, insect wings also serve an important role as sensory structures, providing rapid feedback about wing bending that is used to stabilize flight. While much is known about how wing structure affects aerodynamic performance, the effects of wing structure on sensing remain unexplored. Using a computational model of a flapping wing, we examine how sensing strategies depend on wing stiffness and sensor properties. We show that body rotations can be accurately detected with a small number of sensors on the wing across a wide range of conditions. Optimal sensor locations are clustered at either the wing base or wing tip, depending on a combination of wing stiffness and sensor properties. Moreover, sensing performance is robust to multiple kinds of perturbations. Our work provides a basis for understanding how wing structure impacts incoming sensory information during flight.

Maximally efficient prediction in the early fly visual system may support evasive flight maneuvers

The visual system must make predictions to compensate for inherent delays in its processing. Yet little is known, mechanistically, about how prediction aids natural behaviors. Here, we show that despite a 20-30ms intrinsic processing delay, the vertical motion sensitive (VS) network of the blowfly achieves maximally efficient prediction. This prediction enables the fly to fine-tune its complex, yet brief, evasive flight maneuvers according to its initial ego-rotation at the time of detection of the visual threat. Combining a rich database of behavioral recordings with detailed compartmental modeling of the VS network, we further show that the VS network has axonal gap junctions that are critical for optimal prediction. During evasive maneuvers, a VS subpopulation that directly innervates the neck motor center can convey predictive information about the fly’s future ego-rotation, potentially crucial for ongoing flight control. These results suggest a novel sensory-motor pathway that links sensory prediction to behavior.

Survival-critical behaviors shape neural circuits to translate sensory information into strikingly fast predictions, e.g. in escaping from a predator faster than the system’s processing delay. We show that the fly visual system implements fast and accurate prediction of its visual experience. This provides crucial information for directing fast evasive maneuvers that unfold over just 40ms. Our work shows how this fast prediction is implemented, mechanistically, and suggests the existence of a novel sensory-motor pathway from the fly visual system to a wing steering motor neuron. Echoing and amplifying previous work in the retina, our work hypothesizes that the efficient encoding of predictive information is a universal design principle supporting fast, natural behaviors.

Timing precision in fly flight control: integrating mechanosensory input with muscle physiology

Animals rapidly collect and act on incoming information to navigate complex environments, making the precise timing of sensory feedback critical in the context of neural circuit function. Moreover, the timing of sensory input determines the biomechanical properties of muscles that undergo cyclic length changes, as during locomotion. Both of these issues come to a head in the case of flying insects, as these animals execute steering manoeuvres at timescales approaching the upper limits of performance for neuromechanical systems. Among insects, flies stand out as especially adept given their ability to execute manoeuvres that require sub-millisecond control of steering muscles. Although vision is critical, here I review the role of rapid, wingbeat-synchronous mechanosensory feedback from the wings and structures unique to flies, the halteres. The visual system and descending interneurons of the brain employ a spike rate coding scheme to relay commands to the wing steering system. By contrast, mechanosensory feedback operates at faster timescales and in the language of motor neurons, i.e. spike timing, allowing wing and haltere input to dynamically structure the output of the wing steering system. Although the halteres have been long known to provide essential input to the wing steering system as gyroscopic sensors, recent evidence suggests that the feedback from these vestigial hindwings is under active control. Thus, flies may accomplish manoeuvres through a conserved hindwing circuit, regulating the firing phase-and thus, the mechanical power output-of the wing steering muscles.

Reconstructing full-field flapping wing dynamics from sparse measurements

Flapping insect wings deform during flight. This deformation benefits the insect's aerodynamic force production as well as energetic efficiency. However, it is challenging to measure wing displacement field in flying insects. Many points must be tracked over the wing's surface to resolve its instantaneous shape. To reduce the number of points one is required to track, we propose a physics-based reconstruction method called system equivalent reduction expansion processes to estimate wing deformation and strain from sparse measurements. Measurement locations are determined using a weighted normalized modal displacement method. We experimentally validate the reconstruction technique by flapping a paper wing from 5-9 Hz with 45° and measuring strain at three locations. Two measurements are used for the reconstruction and the third for validation. Strain reconstructions had a maximal error of 30% in amplitude. We extend this methodology to a more realistic insect wing through numerical simulation. We show that wing displacement can be estimated from sparse displacement or strain measurements, and that additional sensors spatially average measurement noise to improve reconstruction accuracy. This research helps overcome some of the challenges of measuring full-field dynamics in flying insects and provides a framework for strain-based sensing in insect-inspired flapping robots.

Coriolis and centrifugal forces drive haltere deformations and influence spike timing

The halteres of flies are mechanosensory organs that serve a crucial role in the control of agile flight, providing sensory input for rapid course corrections to perturbations. Derived from hind wings, halteres are actively flapped and are thus subject to a variety of inertial forces as the fly undergoes complex flight trajectories. Previous analyses of halteres modelled them as a point mass, showing that Coriolis forces lead to subtle deflections orthogonal to the plane of flapping. By design, these models could not consider the effects of force gradients associated with a mass distribution, nor could they reveal three-dimensional spatio-temporal patterns of strain that result from those forces. In addition, diversity in the geometry of halteres, such as shape and asymmetries, could not be simply modelled with a point mass on a massless rod. To study the effects of mass distributions and asymmetries, we examine the haltere subject to both flapping and body rotations using three-dimensional finite-element simulations. We focus on a set of simplified geometries, in which we vary the stalk and bulb shape. We find that haltere mass distribution gives rise to two unreported deformation modes: (i) halteres twist with a magnitude that strongly depends on stalk and bulb geometry and (ii) halteres with an asymmetric mass distribution experience out-of-plane bending due to centrifugal forces, independent of body rotation. Since local strains at the base of the haltere drive deformations of mechanosensory neurons, we combined measured neural encoding mechanisms with our structural analyses to predict the spatial and temporal patterns of neural activity. This activity depends on both the flapping and rotation dynamics, and we show how the timing of neural activity is a viable mechanism for rotation-rate encoding. Our results provide new insights in haltere dynamics and show the viability for timing-based encoding of fly body rotations by halteres.

Sensory processing by motoneurons: a numerical model for low-level flight control in flies

Rhythmic locomotor behaviour in animals requires exact timing of muscle activation within the locomotor cycle. In rapidly oscillating motor systems, conventional control strategies may be affected by neural delays, making these strategies inappropriate for precise timing control. In flies, wing control thus requires sensory processing within the peripheral nervous system, circumventing the central brain. The underlying mechanism, with which flies integrate graded depolarization of visual interneurons and spiking proprioceptive feedback for precise muscle activation, is under debate. Based on physiological parameters, we developed a numerical model of spike initiation in flight muscles of a blowfly. The simulated Hodgkin–Huxley neuron reproduces multiple experimental findings and explains on the cellular level how vision might control wing kinematics. Sensory processing by single motoneurons appears to be sufficient for control of muscle power during flight in flies and potentially other flying insects, reducing computational load on the central brain during body posture reflexes and manoeuvring flight.

Flies Regulate Wing Motion via Active Control of a Dual-Function Gyroscope

Flies execute their remarkable aerial maneuvers using a set of wing steering muscles, which are activated at specific phases of the stroke cycle [1-3]. The activation phase of these muscles-which determines their biomechanical output [4-6]-arises via feedback from mechanoreceptors at the base of the wings and structures unique to flies called halteres [7-9]. Evolved from the hindwings, the tiny halteres oscillate at the same frequency as the wings, although they serve no aerodynamic function [10] and are thought to act as gyroscopes [10-15]. Like the wings, halteres possess minute control muscles whose activity is modified by descending visual input [16], raising the possibility that flies control wing motion by adjusting the motor output of their halteres, although this hypothesis has never been directly tested. Here, using genetic techniques possible in Drosophila melanogaster, we tested the hypothesis that visual input during flight modulates haltere muscle activity and that this, in turn, alters the mechanosensory feedback that regulates the wing steering muscles. Our results suggest that rather than acting solely as a gyroscope to detect body rotation, halteres also function as an adjustable clock to set the spike timing of wing motor neurons, a specialized capability that evolved from the generic flight circuitry of their four-winged ancestors. In addition to demonstrating how the efferent control loop of a sensory structure regulates wing motion, our results provide insight into the selective scenario that gave rise to the evolution of halteres.

Inertial Sensing and Encoding of Self-Motion: Structural and Functional Similarities across Metazoan Taxa

To properly orient and navigate, moving animals must obtain information about the position and motion of their bodies. Animals detect inertial signals resulting from body accelerations and rotations using a variety of sensory systems. In this review, we briefly summarize current knowledge on inertial sensing across widely disparate animal taxa with an emphasis on neuronal coding and sensory transduction. We outline systems built around mechanosensory hair cells, including the chordate vestibular complex and the statocysts seen in many marine invertebrates. We next compare these to schemes employed by flying insects for managing inherently unstable aspects of flapping flight, built around comparable mechanosensory cells but taking unique advantage of the physics of rotating systems to facilitate motion encoding. Finally, we highlight fundamental similarities across taxa with respect to the partnering of inertial senses with visual senses and conclude with a discussion of the functional utility of maintaining a multiplicity of encoding schemes for self-motion information.

Fins as Mechanosensors for Movement and Touch-Related Behaviors

Mechanosensation is a universal feature of animals that is essential for behavior, allowing detection of animals' own body movement and position as well as physical characteristics of the environment. The extraordinary morphological and behavioral diversity that exists across fish species provide rich opportunities for comparative mechanosensory studies in fins. The fins of fishes have been found to function as proprioceptors, by providing feedback on fin ray position and movement, and as tactile sensors, by encoding pressures applied to the fin surface. Across fish species, and among fins, the afferent response is remarkably consistent, suggesting that the ability of fin rays and membrane to sense deformation is a fundamental feature of fish fins. While fin mechanosensation has been known in select, often highly specialized, species for decades, only in the last decade have we explored mechanosensation in typical propulsive fins and considered its role in behavior, particularly locomotion. In this paper, we synthesize the current understanding of the anatomy and physiology of fin mechanosensation, looking toward key directions for research. We argue that a mechanosensory perspective informs studies of fin-based propulsion and other fin-driven behaviors and should be considered in the interpretation of fin morphology and behavior. In addition, we compare the mechanosensory system innervating the fins of fishes to the systems innervating the limbs of mammals and wings of insects in order to identify shared mechanosensory strategies and how different organisms have evolved to meet similar functional challenges. Finally, we discuss how understanding the biological organization and function of fin sensors can inform the design of control systems for engineered fins and fin-driven robotics.

Insect and insect-inspired aerodynamics: unsteadiness, structural mechanics and flight control

Flying insects impress by their versatility and have been a recurrent source of inspiration for engineering devices. A large body of literature has focused on various aspects of insect flight, with an essential part dedicated to the dynamics of flapping wings and their intrinsically unsteady aerodynamic mechanisms. Insect wings flex during flight and a better understanding of structural mechanics and aeroelasticity is emerging. Most recently, insights from solid and fluid mechanics have been integrated with physiological measurements from visual and mechanosensors in the context of flight control in steady airs and through turbulent conditions. We review the key recent advances concerning flight in unsteady environments and how the multi-body mechanics of the insect structure-wings and body-are at the core of the flight control question. The issues herein should be considered when applying bio-informed design principles to robotic flapping wings.

Sensory Feedback and Animal Locomotion: Perspectives from Biology and Biorobotics: An Introduction to the Symposium

The successful completion of many behaviors relies on sensory feedback. This symposium brought together researchers using novel techniques to study how different stimuli are encoded, how and where multimodal feedback is integrated, and how feedback modulates motor output in diverse modes of locomotion (aerial, aquatic, and terrestrial) in a diverse range of taxa (insects, fish, tetrapods), and in robots. Similar to biological organisms, robots can be equipped with integrated sensors and can rely on sensory feedback to adjust the output signal of a controller. Engineers often look to biology for inspiration on how animals have evolved solutions to problems similar to those experienced in robotic movement. Similarly, biologists too must proactively engage with engineers to apply computer and robotic models to test hypotheses and answer questions on the capacity and roles of sensory feedback in generating effective movement. Through a diverse group of researchers, including both biologists and engineers, the symposium attempted to catalyze new interdisciplinary collaborations and identify future research directions for the development of bioinspired sensory control systems, as well as the use of robots to test hypotheses in neuromechanics.

Single mechanosensory neurons encode lateral displacements using precise spike timing and thresholds

During locomotion, animals rely on multiple sensory modalities to maintain stability. External cues may guide behaviour, but they must be interpreted in the context of the animal's own body movements. Mechanosensory cues that can resolve dynamic internal and environmental conditions, like those from vertebrate vestibular systems or other proprioceptors, are essential for guided movement. How do afferent proprioceptor neurons transform movement into a neural code? In flies, modified hindwings known as halteres detect forces produced by body rotations and are essential for flight. However, the mechanisms by which haltere neurons transform forces resulting from three-dimensional body rotations into patterns of neural spikes are unknown. We use intracellular electrodes to record from haltere primary afferent neurons during a range of haltere motions. We find that spike timing activity of individual neurons changes with displacement and propose a mechanism by which single neurons can encode three-dimensional haltere movements during flight.

Neural-inspired sensors enable sparse, efficient classification of spatiotemporal data

Winged insects perform remarkable aerial feats in uncertain, complex fluid environments. This ability is enabled by sensation of mechanical forces to inform rapid corrections in body orientation. Curiously, mechanoreceptor neurons do not faithfully report forces; instead, they are activated by specific time histories of forcing. We find that, far from being a bug, neural encoding by biological sensors is a feature that acts as built-in temporal filtering superbly matched to detect body rotation. Indeed, this encoding further enables surprisingly efficient detection using only a small handful of neurons at key locations. Nature suggests smart data as an alternative strategy to big data, and neural-inspired sensors establish a paradigm in hyperefficient sensing of complex systems.

Sparse sensor placement is a central challenge in the efficient characterization of complex systems when the cost of acquiring and processing data is high. Leading sparse sensing methods typically exploit either spatial or temporal correlations, but rarely both. This work introduces a sparse sensor optimization that is designed to leverage the rich spatiotemporal coherence exhibited by many systems. Our approach is inspired by the remarkable performance of flying insects, which use a few embedded strain-sensitive neurons to achieve rapid and robust flight control despite large gust disturbances. Specifically, we identify neural-inspired sensors at a few key locations on a flapping wing that are able to detect body rotation. This task is particularly challenging as the rotational twisting mode is three orders of magnitude smaller than the flapping modes. We show that nonlinear filtering in time, built to mimic strain-sensitive neurons, is essential to detect rotation, whereas instantaneous measurements fail. Optimized sparse sensor placement results in efficient classification with approximately 10 sensors, achieving the same accuracy and noise robustness as full measurements consisting of hundreds of sensors. Sparse sensing with neural-inspired encoding establishes an alternative paradigm in hyperefficient, embodied sensing of spatiotemporal data and sheds light on principles of biological sensing for agile flight control.

Beyond aerodynamics: The critical roles of the circulatory and tracheal systems in maintaining insect wing functionality

Insect wings consist almost entirely of lifeless cuticle; yet their veins host a complex multimodal sensory apparatus and other tissues that require a continuous supply of water, nutrients and oxygen. This review provides a survey of the various living components in insect wings, as well as the specific contribution of the circulatory and tracheal systems to provide all essential substances. In most insects, hemolymph circulates through the veinal network in a loop flow caused by the contraction of accessory pulsatile organs in the thorax. In other insects, hemolymph oscillates into and out of the wings due to the complex interaction of several factors, such as heartbeat reversal, intermittent pumping of the accessory pulsatile organs in the thorax, and the elasticity of the wall of a special type of tracheae. A practically unexplored subject is the need for continuous hydration of the wing cuticle to retain its flexibility and toughness, including the associated problem of water loss due to evaporation. Also, widely neglected is the influence of the hemolymph mass and the circulating flow in the veins on the aerodynamic properties of insect wings during flight. Ventilation of the extraordinarily long wing tracheae is probably accomplished by intricate interactions with the circulatory system, and by the exchange of oxygen via cutaneous respiration.

Identification of optimal feedback control rules from micro-quadrotor and insect flight trajectories

This paper presents "optimal identification," a framework for using experimental data to identify the optimality conditions associated with the feedback control law implemented in the measurements. The technique compares closed loop trajectory measurements against a reduced order model of the open loop dynamics, and uses linear matrix inequalities to solve an inverse optimal control problem as a convex optimization that estimates the controller optimality conditions. In this study, the optimal identification technique is applied to two examples, that of a millimeter-scale micro-quadrotor with an engineered controller on board, and the example of a population of freely flying Drosophila hydei maneuvering about forward flight. The micro-quadrotor results show that the performance indices used to design an optimal flight control law for a micro-quadrotor may be recovered from the closed loop simulated flight trajectories, and the Drosophila results indicate that the combined effect of the insect longitudinal flight control sensing and feedback acts principally to regulate pitch rate.

Neural evidence supports a dual sensory-motor role for insect wings

Flying insects use feedback from various sensory modalities including vision and mechanosensation to navigate through their environment. The rapid speed of mechanosensory information acquisition and processing compensates for the slower processing times associated with vision, particularly under low light conditions. While halteres in dipteran species are well known to provide such information for flight control, less is understood about the mechanosensory roles of their evolutionary antecedent, wings. The features that wing mechanosensory neurons (campaniform sensilla) encode remains relatively unexplored. We hypothesized that the wing campaniform sensilla of the hawkmoth, Manduca sexta, rapidly and selectively extract mechanical stimulus features in a manner similar to halteres. We used electrophysiological and computational techniques to characterize the encoding properties of wing campaniform sensilla. To accomplish this, we developed a novel technique for localizing receptive fields using a focused IR laser that elicits changes in the neural activity of mechanoreceptors. We found that (i) most wing mechanosensors encoded mechanical stimulus features rapidly and precisely, (ii) they are selective for specific stimulus features, and (iii) there is diversity in the encoding properties of wing campaniform sensilla. We found that the encoding properties of wing campaniform sensilla are similar to those for haltere neurons. Therefore, it appears that the neural architecture that underlies the haltere sensory function is present in wings, which lends credence to the notion that wings themselves may serve a similar sensory function. Thus, wings may not only function as the primary actuator of the organism but also as sensors of the inertial dynamics of the animal.

Evolution of Biological Image Stabilization

The use of vision to coordinate behavior requires an efficient control design that stabilizes the world on the retina or directs the gaze towards salient features in the surroundings. With a level gaze, visual processing tasks are simplified and behaviorally relevant features from the visual environment can be extracted. No matter how simple or sophisticated the eye design, mechanisms have evolved across phyla to stabilize gaze. In this review, we describe functional similarities in eyes and gaze stabilization reflexes, emphasizing their fundamental role in transforming sensory information into motor commands that support postural and locomotor control. We then focus on gaze stabilization design in flying insects and detail some of the underlying principles. Systems analysis reveals that gaze stabilization often involves several sensory modalities, including vision itself, and makes use of feedback as well as feedforward signals. Independent of phylogenetic distance, the physical interaction between an animal and its natural environment - its available senses and how it moves - appears to shape the adaptation of all aspects of gaze stabilization.

Haltere morphology and campaniform sensilla arrangement across Diptera

One of the primary specializations of true flies (order Diptera) is the modification of the hind wings into club-shaped halteres. Halteres are complex mechanosensory structures that provide sensory feedback essential for stable flight control via an array of campaniform sensilla at the haltere base. The morphology of these sensilla has previously been described in a small number of dipteran species, but little is known about how they vary across fly taxa. Using a synoptic set of specimens representing 42 families from all of the major infraorders of Diptera, we used scanning electron microscopy to map the gross and fine structures of halteres, including sensillum shape and arrangement. We found that several features of haltere morphology correspond with dipteran phylogeny: Schizophora generally have smaller halteres with stereotyped and highly organized sensilla compared to nematoceran flies. We also found a previously undocumented high variation of haltere sensillum shape in nematoceran dipterans, as well as the absence of a dorsal sensillum field in multiple families. Overall, variation in haltere sensillar morphology across the dipteran phylogeny provides insight into the evolution of a highly specialized proprioceptive organ and a basis for future studies on haltere sensory function.

Cross-modal influence of mechanosensory input on gaze responses to visual motion in Drosophila

Animals typically combine inertial and visual information to stabilize their gaze against confounding self-generated visual motion, and to maintain a level gaze when the body is perturbed by external forces. In vertebrates, an inner ear vestibular system provides information about body rotations and accelerations, but gaze stabilization is less understood in insects, which lack a vestibular organ. In flies, the halteres, reduced hindwings imbued with hundreds of mechanosensory cells, sense inertial forces and provide input to neck motoneurons that control gaze. These neck motoneurons also receive input from the visual system. Head movement responses to visual motion and physical rotations of the body have been measured independently, but how inertial information might influence gaze responses to visual motion has not been fully explored. We measured the head movement responses to visual motion in intact and haltere-ablated tethered flies to explore the haltere's role in modulating visually-guided head movements in the absence of rotation. We note that visually-guided head movements occur only during flight. Although halteres are not necessary for head movements, the amplitude of the response is smaller in haltereless flies at higher speeds of visual motion. This modulation occurred in the absence of rotational body movements, demonstrating that the inertial forces associated with straight tethered flight are important for gaze-control behavior. The cross-modal influence of halteres on the fly's responses to fast visual motion indicates that the haltere's role in gaze stabilization extends beyond its canonical function as a sensor of angular rotations of the thorax.

Flight control of fruit flies: dynamic response to optic-flow and headwind

Insects are magnificent fliers that are capable of performing many complex tasks such as speed regulation, smooth landings, and collision avoidance, even though their computational abilities are limited by their small brain. To investigate how flying insects respond to changes in wind speed and surrounding optic flow, the open-loop sensorimotor response of female Queensland fruit flies (Bactrocera tryoni) was examined. 136 flies were exposed to stimuli comprising sinusoidally varying optic flow and air flow (simulating forward movement) under tethered conditions in a virtual reality arena. Two responses were measured: the thrust, and the abdomen pitch. The dynamics of the responses to optic flow and air flow were measured at various frequencies, and modelled as a multicompartment linear system, which accurately captures the fruit flies' behavioural responses. The results indicate that these two behavioural responses are concurrently sensitive to changes of optic flow as well as wind. The abdomen pitch showed a streamlining response, where the abdomen was raised higher as the magnitude of either stimulus was increased. The thrust, on the other hand, exhibited a counter-phase response where maximum thrust occurred when the optic flow or wind flow was at a minimum, indicating that the flies were attempting to maintain an ideal flight speed. When the changes in the wind and optic flow were in phase (i.e. did not contradict each other), the net responses (thrust and abdomen pitch) were well approximated by an equally weighted sum of the responses to the individual stimuli. However, when the optic flow and wind stimuli were presented in counterphase, the flies seemed to respond to only one stimulus or the other, demonstrating a form of ‘selective attention’.

The aerodynamics and control of free flight manoeuvres in Drosophila

A firm understanding of how fruit flies hover has emerged over the past two decades, and recent work has focused on the aerodynamic, biomechanical and neurobiological mechanisms that enable them to manoeuvre and resist perturbations. In this review, we describe how flies manipulate wing movement to control their body motion during active manoeuvres, and how these actions are regulated by sensory feedback. We also discuss how the application of control theory is providing new insight into the logic and structure of the circuitry that underlies flight stability.This article is part of the themed issue 'Moving in a moving medium: new perspectives on flight'.

Dipteran Halteres: Perspectives on Function and Integration for a Unique Sensory Organ

The halteres of dipteran insects (true flies) are essential mechanosensory organs for flight. These are modified hindwings with several arrays of sensory cells at their base, and they are one of the characteristic features of flies. Mechanosensory information from the halteres is sent with low latency to wing-steering and head movement motoneurons, allowing direct control of body position and gaze. Analyses of the structure and dynamics of halteres indicate that they experience very small aerodynamic forces but significant inertial forces, including Coriolis forces associated with body rotations. The sensory cells at the base of the haltere detect these forces and allow the fly to correct for perturbations during flight, but new evidence suggests that this may not be their only role. This review will examine our current understanding of how these organs move, encode forces, and transmit information about these forces to the nervous system to guide behavior.