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.

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.].

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.

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.

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.

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

Vibrations through substrates are an important source of information for diverse organisms, from nematodes to elephants. The fundamental challenge for small animals using vibrational communication is to move their limited mass fast enough to provide sufficient kinetic energy for effective information transfer through the substrate whilst optimising energy efficiency over repeated cycles. Here, we describe a vibratory organ found across a commercially important group of plant-feeding insects, the planthoppers (Hemiptera: Fulgoromorpha). This elastic recoil snapping organ generates substrate-borne broadband vibrations using fast, cyclical abdominal motion that transfers kinetic energy to the substrate through the legs. Elastic potential energy is stored and released twice using two different latched energy-storage mechanisms, each utilising a different form of elastic recoil to increase the speed of motion. Comparison to the acoustic tymbal organ of cicadas (Hemiptera: Cicadomorpha) reveals functional convergence in their use of elastic mechanisms to increase the efficacy of mechanical communication.

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.

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.

Terminal attack trajectories of peregrine falcons are described by the proportional navigation guidance law of missiles.

The ability to intercept uncooperative targets is key to many diverse flight behaviors, from courtship to predation. Previous research has looked for simple geometric rules describing the attack trajectories of animals, but the underlying feedback laws have remained obscure. Here, we use GPS loggers and onboard video cameras to study peregrine falcons, Falco peregrinus, attacking stationary targets, maneuvering targets, and live prey. We show that the terminal attack trajectories of peregrines are not described by any simple geometric rule as previously claimed, and instead use system identification techniques to fit a phenomenological model of the dynamical system generating the observed trajectories. We find that these trajectories are best-and exceedingly well-modeled by the proportional navigation (PN) guidance law used by most guided missiles. Under this guidance law, turning is commanded at a rate proportional to the angular rate of the line-of-sight between the attacker and its target, with a constant of proportionality (i.e., feedback gain) called the navigation constant (N). Whereas most guided missiles use navigation constants falling on the interval 3 ≤ N ≤ 5, peregrine attack trajectories are best fitted by lower navigation constants (median N < 3). This lower feedback gain is appropriate at the lower flight speed of a biological system, given its presumably higher error and longer delay. This same guidance law could find use in small visually guided drones designed to remove other drones from protected airspace.

Physics-based simulations of aerial attacks by peregrine falcons reveal that stooping at high speed maximizes catch success against agile prey.

The peregrine falcon Falco peregrinus is renowned for attacking its prey from high altitude in a fast controlled dive called a stoop. Many other raptors employ a similar mode of attack, but the functional benefits of stooping remain obscure. Here we investigate whether, when, and why stooping promotes catch success, using a three-dimensional, agent-based modeling approach to simulate attacks of falcons on aerial prey. We simulate avian flapping and gliding flight using an analytical quasi-steady model of the aerodynamic forces and moments, parametrized by empirical measurements of flight morphology. The model-birds' flight control inputs are commanded by their guidance system, comprising a phenomenological model of its vision, guidance, and control. To intercept its prey, model-falcons use the same guidance law as missiles (pure proportional navigation); this assumption is corroborated by empirical data on peregrine falcons hunting lures. We parametrically vary the falcon's starting position relative to its prey, together with the feedback gain of its guidance loop, under differing assumptions regarding its errors and delay in vision and control, and for three different patterns of prey motion. We find that, when the prey maneuvers erratically, high-altitude stoops increase catch success compared to low-altitude attacks, but only if the falcon's guidance law is appropriately tuned, and only given a high degree of precision in vision and control. Remarkably, the optimal tuning of the guidance law in our simulations coincides closely with what has been observed empirically in peregrines. High-altitude stoops are shown to be beneficial because their high airspeed enables production of higher aerodynamic forces for maneuvering, and facilitates higher roll agility as the wings are tucked, each of which is essential to catching maneuvering prey at realistic response delays.

Head movements quadruple the range of speeds encoded by the insect motion vision system in hawkmoths.

Flying insects use compensatory head movements to stabilize gaze. Like other optokinetic responses, these movements can reduce image displacement, motion and misalignment, and simplify the optic flow field. Because gaze is imperfectly stabilized in insects, we hypothesized that compensatory head movements serve to extend the range of velocities of self-motion that the visual system encodes. We tested this by measuring head movements in hawkmoths Hyles lineata responding to full-field visual stimuli of differing oscillation amplitudes, oscillation frequencies and spatial frequencies. We used frequency-domain system identification techniques to characterize the head's roll response, and simulated how this would have affected the output of the motion vision system, modelled as a computational array of Reichardt detectors. The moths' head movements were modulated to allow encoding of both fast and slow self-motion, effectively quadrupling the working range of the visual system for flight control. By using its own output to drive compensatory head movements, the motion vision system thereby works as an adaptive sensor, which will be especially beneficial in nocturnal species with inherently slow vision. Studies of the ecology of motion vision must therefore consider the tuning of motion-sensitive interneurons in the context of the closed-loop systems in which they function.

In vivo time-resolved microtomography reveals the mechanics of the blowfly flight motor.

Dipteran flies are amongst the smallest and most agile of flying animals. Their wings are driven indirectly by large power muscles, which cause cyclical deformations of the thorax that are amplified through the intricate wing hinge. Asymmetric flight manoeuvres are controlled by 13 pairs of steering muscles acting directly on the wing articulations. Collectively the steering muscles account for <3% of total flight muscle mass, raising the question of how they can modulate the vastly greater output of the power muscles during manoeuvres. Here we present the results of a synchrotron-based study performing micrometre-resolution, time-resolved microtomography on the 145 Hz wingbeat of blowflies. These data represent the first four-dimensional visualizations of an organism's internal movements on sub-millisecond and micrometre scales. This technique allows us to visualize and measure the three-dimensional movements of five of the largest steering muscles, and to place these in the context of the deforming thoracic mechanism that the muscles actuate. Our visualizations show that the steering muscles operate through a diverse range of nonlinear mechanisms, revealing several unexpected features that could not have been identified using any other technique. The tendons of some steering muscles buckle on every wingbeat to accommodate high amplitude movements of the wing hinge. Other steering muscles absorb kinetic energy from an oscillating control linkage, which rotates at low wingbeat amplitude but translates at high wingbeat amplitude. Kinetic energy is distributed differently in these two modes of oscillation, which may play a role in asymmetric power management during flight control. Structural flexibility is known to be important to the aerodynamic efficiency of insect wings, and to the function of their indirect power muscles. We show that it is integral also to the operation of the steering muscles, and so to the functional flexibility of the insect flight motor.

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.

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.

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.

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.