Obstacle avoidance in aerial pursuit.

Pursuing prey through clutter is a complex and risky activity requiring integration of guidance subsystems for obstacle avoidance and target pursuit. The unobstructed pursuit trajectories of Harris' hawks Parabuteo unicinctus are well modeled by a mixed guidance law feeding back target deviation angle and line-of-sight rate. Here we ask how their pursuit behavior is modified in response to obstacles, using high-speed motion capture to reconstruct flight trajectories recorded during obstructed pursuit of maneuvering targets. We find that Harris' hawks use the same mixed guidance law during obstructed pursuit but appear to superpose a discrete bias command that resets their flight direction to aim at a clearance of approximately one wing length from an upcoming obstacle as they reach some threshold distance from it. Combining a feedback command in response to target motion with a feedforward command in response to upcoming obstacles provides an effective means of prioritizing obstacle avoidance while remaining locked-on to a target. We therefore anticipate that a similar mechanism may be used in terrestrial and aquatic pursuit. The same biased guidance law could also be used for obstacle avoidance in drones designed to intercept other drones in clutter, or to navigate between fixed waypoints in urban environments.

Visual versus visual-inertial guidance in hawks pursuing terrestrial targets.

The aerial interception behaviour of falcons is well modelled by a guidance law called proportional navigation, which commands steering at a rate proportional to the angular rate of the line-of-sight from predator to prey. Because the line-of-sight rate is defined in an inertial frame of reference, proportional navigation must be implemented using visual-inertial sensor fusion. By contrast, the aerial pursuit behaviour of hawks chasing terrestrial targets is better modelled by a mixed guidance law combining information on the line-of-sight rate with information on the deviation angle between the attacker's velocity and the line-of-sight. Here we ask whether this behaviour may be controlled using visual information alone. We use high-speed motion capture to record n = 228 flights from N = 4 Harris' hawks Parabuteo unicinctus, and show that proportional navigation and mixed guidance both model their trajectories well. The mixed guidance law also models the data closely when visual-inertial information on the line-of-sight rate is replaced by visual information on the motion of the target relative to its background. Although the visual-inertial form of the mixed guidance law provides the closest fit, all three guidance laws provide an adequate phenomenological model of the behavioural data, whilst making different predictions on the physiological pathways involved.

Through Hawks' Eyes: Synthetically Reconstructing the Visual Field of a Bird in Flight.

Birds of prey rely on vision to execute flight manoeuvres that are key to their survival, such as intercepting fast-moving targets or navigating through clutter. A better understanding of the role played by vision during these manoeuvres is not only relevant within the field of animal behaviour, but could also have applications for autonomous drones. In this paper, we present a novel method that uses computer vision tools to analyse the role of active vision in bird flight, and demonstrate its use to answer behavioural questions. Combining motion capture data from Harris' hawks with a hybrid 3D model of the environment, we render RGB images, semantic maps, depth information and optic flow outputs that characterise the visual experience of the bird in flight. In contrast with previous approaches, our method allows us to consider different camera models and alternative gaze strategies for the purposes of hypothesis testing, allows us to consider visual input over the complete visual field of the bird, and is not limited by the technical specifications and performance of a head-mounted camera light enough to attach to a bird's head in flight. We present pilot data from three sample flights: a pursuit flight, in which a hawk intercepts a moving target, and two obstacle avoidance flights. With this approach, we provide a reproducible method that facilitates the collection of large volumes of data across many individuals, opening up new avenues for data-driven models of animal behaviour. Supplementary Information: The online version contains supplementary material available at 10.1007/s11263-022-01733-2.

Lessons from natural flight for aviation: then, now and tomorrow.

Powered flight was once a capability limited only to animals, but by identifying useful attributes of animal flight and building on these with technological advances, engineers have pushed the frontiers of flight beyond our predecessors' wildest imaginations. Yet, there remain many key characteristics of biological flight that elude current aircraft design, motivating a careful re-analysis of what we have learned from animals already, and how this has been revealed experimentally, as well as a specific focus on identifying what remains unknown. Here, we review the literature to identify key contributions that began in biology and have since been translated into aeronautical devices or capabilities. We identify central areas for future research and highlight the importance of maintaining an open line of two-way communication between biologists and engineers. Such interdisciplinary, bio-informed analyses continue to push forward the frontiers of aeronautics and experimental biology alike.

Sexual selection and predation drive the repeated evolution of stridulation in Heteroptera and other arthropods.

Acoustic and substrate-borne vibrations are among the most widely used signalling modalities in animals. Arthropods display a staggering diversity of vibroacoustic organs generating acoustic sound and/or substrate-borne vibrations, and are fundamental to our broader understanding of the evolution of animal signalling. The primary mechanism that arthropods use to generate vibroacoustic signals is stridulation, which involves the rubbing together of opposing body parts. Although stridulation is common, its behavioural context and evolutionary drivers are often hard to pinpoint, owing to limited synthesis of empirical observations on stridulatory species. This is exacerbated by the diversity of mechanisms involved and the sparsity of their description in the literature, which renders their documentation a challenging task. Here, we present the most comprehensive review to date on the systematic distribution and behavioural context of stridulation. We use the megadiverse heteropteran insects as a model, together with multiple arthropod outgroups (arachnids, myriapods, and selected pancrustaceans). We find that stridulatory vibroacoustic signalling has evolved independently at least 84 times and is present in roughly 20% of Heteroptera, representing a remarkable case of convergent evolution. By studying the behavioural context of stridulation across Heteroptera and 189 outgroup lineages, we find that predation pressure and sexual selection are the main behaviours associated with stridulation across arthropods, adding further evidence for their role as drivers of large-scale signalling and morphological innovation in animals. Remarkably, the absence of tympanal ears in most Heteroptera suggests that they typically cannot detect the acoustic component of their stridulatory signals. This demonstrates that the adoption of new signalling modalities is not always correlated with the ability to perceive those signals, especially when these signals are directed towards interspecific receivers in defensive contexts. Furthermore, by mapping their morphology and systematic distribution, we show that stridulatory organs tend to evolve in specific body parts, likely originating from cleaning motions and pre-copulatory displays that are common to most arthropods. By synthesising our understanding of stridulation and stridulatory organs across major arthropod groups, we create the necessary framework for future studies to explore their systematic and behavioural significance, their potential role in sensory evolution and innovation, and the biomechanics of this mode of signalling.

Gap selection and steering during obstacle avoidance in pigeons.

The ability of birds to fly through cluttered environments has inspired biologists interested in understanding its underlying mechanisms, and engineers interested in applying its underpinning principles. To analyse this problem empirically, we break it down into two distinct, but related, questions: How do birds select which gaps to aim for? And how do they steer through them? We answered these questions using a combined experimental and modelling approach, in which we released pigeons (Columbia livia domestica) inside a large hall with an open exit separated from the release point by a curtain creating two vertical gaps - one of which was obstructed by an obstacle. We tracked the birds using a high-speed motion capture system, and found that their gap choice seemed to be biased by their intrinsic handedness, rather than determined by extrinsic cues such as the size of the gap or its alignment with the destination. We modelled the pigeons' steering behaviour algorithmically by simulating their flight trajectories under a set of six candidate guidance laws, including those used previously to model target-oriented flight behaviours in birds. We found that their flights were best modelled by delayed proportional navigation commanding turning in proportion to the angular rate of the line-of-sight from the pigeon to the midpoint of the gap. Our results are consistent with this being a two-phase behaviour, in which the pigeon heads forward from the release point before steering towards the midpoint of whichever gap it chooses to aim for under closed-loop guidance. Our findings have implications for the sensorimotor mechanisms that underlie clutter negotiation in birds, uniting this with other kinds of target-oriented behaviours including aerial pursuit.

Raptors avoid the confusion effect by targeting fixed points in dense aerial prey aggregations.

Collective behaviours are widely assumed to confuse predators, but empirical support for a confusion effect is often lacking, and its importance must depend on the predator's targeting mechanism. Here we show that Swainson's Hawks Buteo swainsoni and other raptors attacking swarming Mexican Free-tailed Bats Tadarida brasiliensis steer by turning towards a fixed point in space within the swarm, rather than by using closed-loop pursuit of any one individual. Any prey with which the predator is on a collision course will appear to remain on a constant bearing, so target selection emerges naturally from the geometry of a collision. Our results show how predators can simplify the demands on their sensory system by decoupling steering from target acquisition when capturing prey from a dense swarm. We anticipate that the same tactic will be used against flocks and schools across a wide range of taxa, in which case a confusion effect is paradoxically more likely to occur in attacks on sparse groups, for which steering and target acquisition cannot be decoupled.

Optimization of dynamic soaring in a flap-gliding seabird affects its large-scale distribution at sea.

Dynamic soaring harvests energy from a spatiotemporal wind gradient, allowing albatrosses to glide over vast distances. However, its use is challenging to demonstrate empirically and has yet to be confirmed in other seabirds. Here, we investigate how flap-gliding Manx shearwaters optimize their flight for dynamic soaring. We do so by deriving a new metric, the horizontal wind effectiveness, that quantifies how effectively flight harvests energy from a shear layer. We evaluate this metric empirically for fine-scale trajectories reconstructed from bird-borne video data using a simplified flight dynamics model. We find that the birds' undulations are phased with their horizontal turning to optimize energy harvesting. We also assess the opportunity for energy harvesting in long-range, GPS-logged foraging trajectories and find that Manx shearwaters optimize their flight to increase the opportunity for dynamic soaring during favorable wind conditions. Our results show how small-scale dynamic soaring affects large-scale Manx shearwater distribution at sea.

Optimization of avian perching manoeuvres.

Perching at speed is among the most demanding flight behaviours that birds perform1,2 and is beyond the capability of most autonomous vehicles. Smaller birds may touch down by hovering3-8, but larger birds typically swoop up to perch1,2-presumably because the adverse scaling of their power margin prohibits hovering9 and because swooping upwards transfers kinetic to potential energy before collision1,2,10. Perching demands precise control of velocity and pose11-14, particularly in larger birds for which scale effects make collisions especially hazardous6,15. However, whereas cruising behaviours such as migration and commuting typically minimize the cost of transport or time of flight16, the optimization of such unsteady flight manoeuvres remains largely unexplored7,17. Here we show that the swooping trajectories of perching Harris' hawks (Parabuteo unicinctus) minimize neither time nor energy alone, but rather minimize the distance flown after stalling. By combining motion capture data from 1,576 flights with flight dynamics modelling, we find that the birds' choice of where to transition from powered dive to unpowered climb minimizes the distance over which high lift coefficients are required. Time and energy are therefore invested to provide the control authority needed to glide safely to the perch, rather than being minimized directly as in technical implementations of autonomous perching under nonlinear feedback control12 and deep reinforcement learning18,19. Naive birds learn this behaviour on the fly, so our findings suggest a heuristic principle that could guide reinforcement learning of autonomous perching.

Slit sense organ distribution on the legs of two species of orb-weaving spider (Araneae: Araneidae).

Biotic and abiotic mechanical stimuli are ubiquitous in the environment, and are a widely used source of sensory information in arthropods. Spiders sense mechanical stimuli using hundreds of slit sense organs (small isolated slits, large isolated slits, groups of slits and lyriform organs) distributed across their bodies and appendages. These slit sense organs are embedded in the exoskeleton and detect cuticular strain. Therefore, the spatial pattern of these sensors can give clues into how mechanical stimuli from different sources might be processed and filtered as they are transmitted through the body. Here, we map the distribution of slit sense organs on the legs in two species of orb-weaving spider, A. diadematus and T. edulis, in which slit sense organ distribution has not previously been investigated. We image the spiders' legs using scanning electron microscopy, and trace the position and orientation of slits on these images to describe the distribution and external morphology of the slit sense organs. We show that both species have a similar distribution of slit sense organs, with small isolated slits occurring in consistent lines parallel to the long axis of the legs, whilst large isolated slits, groups of slits and lyriform organs appear in fixed positions near the leg joints. Our findings support what has been described in the literature for several other species of spider, which indicates that slit organ arrangement is conserved across spiders in different evolutionary lineages and with disparate hunting strategies. The dispersed distribution of small isolated slits along the whole length of the leg may be used to detect large-scale strain of the leg segment as a result of muscle activity or internal changes in haemolymph pressure.

Aerial attack strategies of hawks hunting bats, and the adaptive benefits of swarming.

Aggregation can reduce an individual's predation risk, by decreasing predator hunting efficiency or displacing predation onto others. Here, we explore how the behaviors of predator and prey influence catch success and predation risk in Swainson's hawks Buteo swainsoni attacking swarming Brazilian free-tailed bats Tadarida brasiliensis on emergence. Lone bats including stragglers have a high relative risk of predation, representing ~5% of the catch but ~0.2% of the population. Attacks on the column were no less successful than attacks on lone bats, so hunting efficiency is not decreased by group vigilance or confusion. Instead, lone bats were attacked disproportionately often, representing ~10% of all attacks. Swarming therefore displaces the burden of predation onto bats outside the column-whether as isolated wanderers not benefitting from dilution through attack abatement, or as peripheral stragglers suffering marginal predation and possible selfish herd effects. In contrast, the hawks' catch success depended only on the attack maneuvers that they employed, with the odds of success being more than trebled in attacks involving a high-speed stoop or rolling grab. Most attacks involved one of these two maneuvers, which therefore represent alternative rather than complementary tactics. Hence, whereas a bat's survival depends on maintaining column formation, a hawk's success does not depend on attacking lone bats-even though their tendency to do so is sufficient to explain the adaptive benefits of their prey's aggregation behavior. A hawk's success instead depends on the flight maneuvers it deploys, including the high-speed stoop that is characteristic of many raptors. Swarming bats emerging from a massive desert roost reduce their predation risk by maintaining tight column formation, because the hawks that predate them attack peripheral stragglers and isolated wanderers disproportionately. Whereas a bat's predation risk depends on maintaining its position within the column, the catch success of a hawk depends on how it maneuvers itself to attack, and is maximized by executing a high-speed dive or rolling grab maneuver.

A semi-empirical model of the aerodynamics of manoeuvring insect flight.

Blade element modelling provides a quick analytical method for estimating the aerodynamic forces produced during insect flight, but such models have yet to be tested rigorously using kinematic data recorded from free-flying insects. This is largely because of the paucity of detailed free-flight kinematic data, but also because analytical limitations in existing blade element models mean that they cannot incorporate the complex three-dimensional movements of the wings and body that occur during insect flight. Here, we present a blade element model with empirically fitted aerodynamic force coefficients that incorporates the full three-dimensional wing kinematics of manoeuvring Eristalis hoverflies, including torsional deformation of their wings. The two free parameters were fitted to a large free-flight dataset comprising N = 26 541 wingbeats, and the fitted model captured approximately 80% of the variation in the stroke-averaged forces in the sagittal plane. We tested the robustness of the model by subsampling the data, and found little variation in the parameter estimates across subsamples comprising 10% of the flight sequences. The simplicity and generality of the model that we present is such that it can be readily applied to kinematic datasets from other insects, and also used for the study of insect flight dynamics.

Attack behaviour in naive gyrfalcons is modelled by the same guidance law as in peregrine falcons, but at a lower guidance gain.

The aerial hunting behaviours of birds are strongly influenced by flight morphology and ecology, but little is known of how this relates to the behavioural algorithms guiding flight. Here, we used GPS loggers to record the attack trajectories of captive-bred gyrfalcons (Falco rusticolus) during their maiden flights against robotic aerial targets, which we compared with existing flight data from peregrine falcons (Falco peregrinus). The attack trajectories of both species were well modelled by a proportional navigation (PN) guidance law, which commands turning in proportion to the angular rate of the line-of-sight to target, at a guidance gain N However, naive gyrfalcons operate at significantly lower values of N than peregrine falcons, producing slower turning and a longer path to intercept. Gyrfalcons are less manoeuvrable than peregrine falcons, but physical constraint is insufficient to explain the lower values of N we found, which may reflect either the inexperience of the individual birds or ecological adaptation at the species level. For example, low values of N promote the tail-chasing behaviour that is typical of wild gyrfalcons and which apparently serves to tire their prey in a prolonged high-speed pursuit. Likewise, during close pursuit of typical fast evasive prey, PN will be less prone to being thrown off by erratic target manoeuvres at low guidance gain. The fact that low-gain PN successfully models the maiden attack flights of gyrfalcons suggests that this behavioural algorithm is embedded in a guidance pathway ancestral to the clade containing gyrfalcons and peregrine falcons, though perhaps with much deeper evolutionary origins.

Correction: Planthopper bugs use a fast, cyclic elastic recoil mechanism for effective vibrational communication at small body size.

[This corrects the article DOI: 10.1371/journal.pbio.3000155.].

An Algorithmic Approach to Natural Behavior.

Uncovering the mechanisms and implications of natural behavior is a goal that unites many fields of biology. Yet, the diversity, flexibility, and multi-scale nature of these behaviors often make understanding elusive. Here, we review studies of animal pursuit and evasion - two special classes of behavior where theory-driven experiments and new modeling techniques are beginning to uncover the general control principles underlying natural behavior. A key finding of these studies is that intricate sequences of pursuit and evasion behavior can often be constructed through simple, repeatable rules that link sensory input to motor output: we refer to these rules as behavioral algorithms. Identifying and mathematically characterizing these algorithms has led to important insights, including the discovery of guidance rules that attacking predators use to intercept mobile prey, and coordinated neural and biomechanical mechanisms that animals use to avoid impending collisions. Here, we argue that algorithms provide a good starting point for studies of natural behavior more generally. Rather than beginning at the neural or ecological levels of organization, we advocate starting in the middle, where the algorithms that link sensory input to behavioral output can provide a solid foundation from which to explore both the implementation and the ecological outcomes of behavior. We review insights that have been gained through such an algorithmic approach to pursuit and evasion behaviors. From these, we synthesize theoretical principles and lay out key modeling tools needed to apply an algorithmic approach to the study of other complex natural behaviors.

On the morphology and evolution of cicadomorphan tymbal organs.

Cicadas and many of their relatives (Hemiptera: Cicadomorpha) generate vibroacoustic signals using tymbal organs located on their first two abdominal segments. Although tymbals are well-studied in Cicadidae, their systematic distribution in other Cicadomorpha and their possible homologies to the vibroacoustic mechanisms of other Hemiptera have been debated for more than a century. In the present study, we re-examine the morphology of the musculoskeletal system of cicadomorphan vibroacoustic organs, and we document their systematic distribution in 78 species drawn from across the phylogeny of Cicadomorpha. We also compare their morphology to the recently-described snapping organ of planthoppers (Fulgoromorpha). Based on the structure and innervation of the metathoracic and abdominal musculoskeletal system, we find that several key elements of cicadomorphan vibroacoustic organs that have previously been assigned to the first abdominal segment in fact belong to the second. We find that tymbal organs are nearly ubiquitous in Cicadomorpha, and conclude based on their phylogenetic distribution, that they are likely to be synapomorphic. The unusual tymbal-like organs of the Deltocephalinae and Typhlocybinae, represent derived modifications. Finally, we propose a standardised terminology for sternal components of the cicadomorphan vibrational organs, which can be used in future taxonomic descriptions.

Motor output and control input in flapping flight: a compact model of the deforming wing kinematics of manoeuvring hoverflies.

Insects are conventionally modelled as controlling flight by varying a few summary kinematic parameters that are defined on a per-wingbeat basis, such as the stroke amplitude, mean stroke angle and mean wing pitch angle. Nevertheless, as insects have tens of flight muscles and vary their kinematics continuously, the true dimension of their control input space is likely to be much higher. Here, we present a compact description of the deforming wing kinematics of 36 manoeuvring Eristalis hoverflies, applying functional principal components analysis to Fourier series fits of the wingtip position and wing twist measured over 26 541 wingbeats. This analysis offers a high degree of data reduction, in addition to insight into the natural kinematic couplings. We used statistical resampling techniques to verify that the principal components (PCs) were repeatable features of the data, and analysed their coefficient vectors to provide insight into the form of these natural couplings. Conceptually, the dominant PCs provide a natural set of control input variables that span the control input subspace utilized by this species, but they can also be thought of as output states of the flight motor. This functional description of the wing kinematics is appropriate to modelling insect flight as a form of limit cycle control.

On the morphology and possible function of two putative vibroacoustic mechanisms in derbid planthoppers (Hemiptera: Fulgoromorpha: Derbidae).

A mechanism involving interaction of the metathoracic wing and third abdominal segment of derbid planthoppers was first discovered over a century ago, and interpreted as a stridulatory organ for sound production. Although referred to occasionally in later taxonomic works, the detailed morphology, systematic distribution, and behavioural significance of this structure have remained unknown, and its proposed use in sound production has never been corroborated. Here we examine the distribution and morphology of the supposed stridulatory organ of Derbidae and the recently-described vibratory mechanism of planthoppers - the snapping organ, across 168 species covering the entire taxonomic spectrum of the family. We find that many derbids possess snapping organs morphologically similar to those of other planthoppers, and find no evidence for the presence of tymbal organs, which were previously thought to generate vibrational signals in derbids. We find the supposed stridulatory mechanism to be widespread in Derbidae, and conclude that it provides several systematically and taxonomically important characters. Nevertheless, its morphology appears unsuitable for the production of sound, and we instead speculate that the mechanism plays a role in spreading chemical secretions or wax. Finally, we observe wax production by tergal glands in derbid larvae, and illustrate their external morphology in adults.

Birds invest wingbeats to keep a steady head and reap the ultimate benefits of flying together.

Flapping flight is the most energetically demanding form of sustained forwards locomotion that vertebrates perform. Flock dynamics therefore have significant implications for energy expenditure. Despite this, no studies have quantified the biomechanical consequences of flying in a cluster flock or pair relative to flying solo. Here, we compared the flight characteristics of homing pigeons (Columba livia) flying solo and in pairs released from a site 7 km from home, using high-precision 5 Hz global positioning system (GPS) and 200 Hz tri-axial accelerometer bio-loggers. As expected, paired individuals benefitted from improved homing route accuracy, which reduced flight distance by 7% and time by 9%. However, realising these navigational gains involved substantial changes in flight kinematics and energetics. Both individuals in a pair increased their wingbeat frequency by 18% by decreasing the duration of their upstroke. This sharp increase in wingbeat frequency caused just a 3% increase in airspeed but reduced the oscillatory displacement of the body by 22%, which we hypothesise relates to an increased requirement for visual stability and manoeuvrability when flying in a flock or pair. The combination of the increase in airspeed and a higher wingbeat frequency would result in a minimum 2.2% increase in the total aerodynamic power requirements if the wingbeats were fully optimised. Overall, the enhanced navigational performance will offset any additional energetic costs as long as the metabolic power requirements are not increased above 9%. Our results demonstrate that the increases in wingbeat frequency when flying together have previously been underestimated by an order of magnitude and force reinterpretation of their mechanistic origin. We show that, for pigeons flying in pairs, two heads are better than one but keeping a steady head necessitates energetically costly kinematics.