Optic flow cues help explain altitude control over sea in freely flying gulls

Honeybees Use Multiple Invariants to Control Their Altitude

How do bees perceive altitude changes so as to produce safe displacements within their environment? It has been proved that humans use invariants, but this concept remains little-known within the entomology community. The use of a single invariant, the optical speed rate of change, has been extensively demonstrated in bees in a ground-following task. Recently, it has been demonstrated that another invariant, the splay angle rate of change, could also be used by bees to adjust their altitude. This study aims to understand how bees use these invariants when they are available simultaneously. This issue has been addressed using an experimental setup providing discordant information to bees. We have shown that when the two invariants were available, bees performed ground-following tasks relying primarily on optical speed rate of change. Conversely, when optical speed rate of change was less easily accessible, splay angle rate of change was prioritized, unless the bees perceive danger. Taken together, these results illustrate how the joint use of several invariants allows bees to produce adaptive behaviors.

Motion vision: Fish swimming to see

Self-motion generates optic flow, a visual motion signal used by many organisms for navigation and self-stabilization. A new study quantitatively demonstrates how environmental structure and current behavioral state explain the spatial biases observed in zebrafish optomotor responses.

Optic flow in the natural habitats of zebrafish supports spatial biases in visual self-motion estimation

Animals benefit from knowing if and how they are moving. Across the animal kingdom, sensory information in the form of optic flow over the visual field is used to estimate self-motion. However, different species exhibit strong spatial biases in how they use optic flow. Here, we show computationally that noisy natural environments favor visual systems that extract spatially biased samples of optic flow when estimating self-motion. The performance associated with these biases, however, depends on interactions between the environment and the animal's brain and behavior. Using the larval zebrafish as a model, we recorded natural optic flow associated with swimming trajectories in the animal's habitat with an omnidirectional camera mounted on a mechanical arm. An analysis of these flow fields suggests that lateral regions of the lower visual field are most informative about swimming speed. This pattern is consistent with the recent findings that zebrafish optomotor responses are preferentially driven by optic flow in the lateral lower visual field, which we extend with behavioral results from a high-resolution spherical arena. Spatial biases in optic-flow sampling are likely pervasive because they are an effective strategy for determining self-motion in noisy natural environments.

Optic flow in the natural habitats of zebrafish supports spatial biases in visual self-motion estimation

Animals benefit from knowing if and how they are moving. Across the animal kingdom, sensory information in the form of optic flow over the visual field is used to estimate self-motion. However, different species exhibit strong spatial biases in how they use optic flow. Here, we show computationally that noisy natural environments favor visual systems that extract spatially biased samples of optic flow when estimating self-motion. The performance associated with these biases, however, depends on interactions between the environment and the animal's brain and behavior. Using the larval zebrafish as a model, we recorded natural optic flow associated with swimming trajectories in the animal's habitat with an omnidirectional camera mounted on a mechanical arm. An analysis of these flow fields suggests that lateral regions of the lower visual field are most informative about swimming speed. This pattern is consistent with the recent findings that zebrafish optomotor responses are preferentially driven by optic flow in the lateral lower visual field, which we extend with behavioral results from a high-resolution spherical arena. Spatial biases in optic-flow sampling are likely pervasive because they are an effective strategy for determining self-motion in noisy natural environments.

Optic flow in the natural habitats of zebrafish supports spatial biases in visual self-motion estimation

Animals benefit from knowing if and how they are moving. Across the animal kingdom, sensory information in the form of optic flow over the visual field is used to estimate self-motion. However, different species exhibit strong spatial biases in how they use optic flow. Here, we show computationally that noisy natural environments favor visual systems that extract spatially biased samples of optic flow when estimating self-motion. The performance associated with these biases, however, depends on interactions between the environment and the animal's brain and behavior. Using the larval zebrafish as a model, we recorded natural optic flow associated with swimming trajectories in the animal's habitat with an omnidirectional camera mounted on a mechanical arm. An analysis of these flow fields suggests that lateral regions of the lower visual field are most informative about swimming speed. This pattern is consistent with the recent findings that zebrafish optomotor responses are preferentially driven by optic flow in the lateral lower visual field, which we extend with behavioral results from a high-resolution spherical arena. Spatial biases in optic-flow sampling are likely pervasive because they are an effective strategy for determining self-motion in noisy natural environments.

Opportunistic soaring by birds suggests new opportunities for atmospheric energy harvesting by flying robots

The use of flying robots (drones) is increasing rapidly, but their utility is limited by high power demand, low specific energy storage and poor gust tolerance. By contrast, birds demonstrate long endurance, harvesting atmospheric energy in environments ranging from cluttered cityscapes to open landscapes, coasts and oceans. Here, we identify new opportunities for flying robots, drawing upon the soaring flight of birds. We evaluate mechanical energy transfer in soaring from first principles and review soaring strategies encompassing the use of updrafts (thermal or orographic) and wind gradients (spatial or temporal). We examine the extent to which state-of-the-art flying robots currently use each strategy and identify several untapped opportunities including slope soaring over built environments, thermal soaring over oceans and opportunistic gust soaring. In principle, the energetic benefits of soaring are accessible to flying robots of all kinds, given atmospherically aware sensor systems, guidance strategies and gust tolerance. Hence, while there is clear scope for specialist robots that soar like albatrosses, or which use persistent thermals like vultures, the greatest untapped potential may lie in non-specialist vehicles that make flexible use of atmospheric energy through path planning and flight control, as demonstrated by generalist flyers such as gulls, kites and crows.

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.

Foraging on the wing for fish while migrating over changing landscapes: traveling behaviors vary with available aquatic habitat for Caspian terns

BACKGROUND

Birds that forage while covering distance during migration should adjust traveling behaviors as the availability of foraging habitat changes. Particularly, the behavior of those species that depend on bodies of water to find food yet manage to migrate over changing landscapes may be limited by the substantial variation in feeding opportunities along the route.

METHODS

Using GPS tracking data, we studied how traveling behaviors vary with available foraging habitat during the long-distance migration of Caspian terns (Hydroprogne caspia), a bird with a specialized diet based on fish that needs bodies of water to forage. We measured individual variation in five traveling behaviors related to foraging along the route and used linear mixed effects models to test the following variables as predictors of traveling behaviors: proportion of overlap with water bodies, weather conditions, days at previous stopover and days of migration. Also, we tested if during traveling days flight height and speed varied with time of day and if birds were in areas with greater proportion of water bodies compared to what would be expected by chance from the landscape.

RESULTS

We found variation in migratory traveling behaviors that was mainly related to the proportion of overlap with water bodies and experienced tailwinds. Suggesting a mixed migratory strategy with fly-and-foraging, Caspian terns reduced travel speed, flew fewer hours of the day, had lower flight heights and increased diurnal over nocturnal migratory flight hours as the proportion of overlap with water bodies increased. Birds had lower flight speeds and higher flight heights during the day, were in foraging habitats with greater proportions of water than expected by chance but avoided foraging detours. Instead, route tortuosity was associated with lower wind support and cloudier skies.

CONCLUSIONS

Our findings show how birds may adjust individual behavior as foraging habitat availability changes during migration and contribute to the growing knowledge on mixed migratory strategies of stopover use and fly-and-forage.

Floor and ceiling mirror configurations to study altitude control in honeybees

To investigate altitude control in honeybees, an optical configuration was designed to manipulate or cancel the optic flow. It has been widely accepted that honeybees rely on the optic flow generated by the ground to control their altitude. Here, we create an optical configuration enabling a better understanding of the mechanism of altitude control in honeybees. This optical configuration aims to mimic some of the conditions that honeybees experience over a natural water body. An optical manipulation, based on a pair of opposed horizontal mirrors, was designed to remove any visual information coming from the floor and ceiling. Such an optical manipulation allowed us to get closer to the seminal experiment of Heran & Lindauer 1963. Zeitschrift für vergleichende Physiologie47, 39-55. (doi:10.1007/BF00342890). Our results confirmed that a reduction or an absence of ventral optic flow in honeybees leads to a loss in altitude, and eventually a collision with the floor.

Lidar-Based Navigation of Subterranean Environments Using Bio-Inspired Wide-Field Integration of Nearness

Navigating unknown environments is an ongoing challenge in robotics. Processing large amounts of sensor data to maintain localization, maps of the environment, and sensible paths can result in high compute loads and lower maximum vehicle speeds. This paper presents a bio-inspired algorithm for efficiently processing depth measurements to achieve fast navigation of unknown subterranean environments. Animals developed efficient sensorimotor convergence approaches, allowing for rapid processing of large numbers of spatially distributed measurements into signals relevant for different behavioral responses necessary to their survival. Using a spatial inner-product to model this sensorimotor convergence principle, environmentally relative states critical to navigation are extracted from spatially distributed depth measurements using derived weighting functions. These states are then applied as feedback to control a simulated quadrotor platform, enabling autonomous navigation in subterranean environments. The resulting outer-loop velocity controller is demonstrated in both a generalized subterranean environment, represented by an infinite cylinder, and nongeneralized environments like tunnels and caves.

Infrasound as a Cue for Seabird Navigation

Seabirds are amongst the most mobile of all animal species and spend large amounts of their lives at sea. They cross vast areas of ocean that appear superficially featureless, and our understanding of the mechanisms that they use for navigation remains incomplete, especially in terms of available cues. In particular, several large-scale navigational tasks, such as homing across thousands of kilometers to breeding sites, are not fully explained by visual, olfactory or magnetic stimuli. Low-frequency inaudible sound, i.e., infrasound, is ubiquitous in the marine environment. The spatio-temporal consistency of some components of the infrasonic wavefield, and the sensitivity of certain bird species to infrasonic stimuli, suggests that infrasound may provide additional cues for seabirds to navigate, but this remains untested. Here, we propose a framework to explore the importance of infrasound for navigation. We present key concepts regarding the physics of infrasound and review the physiological mechanisms through which infrasound may be detected and used. Next, we propose three hypotheses detailing how seabirds could use information provided by different infrasound sources for navigation as an acoustic beacon, landmark, or gradient. Finally, we reflect on strengths and limitations of our proposed hypotheses, and discuss several directions for future work. In particular, we suggest that hypotheses may be best tested by combining conceptual models of navigation with empirical data on seabird movements and in-situ infrasound measurements.

Flight altitude dynamics of migrating European nightjars across regions and seasons

Avian migrants may fly at a range of altitudes, but usually concentrate near strata where a combination of flight conditions is favourable. The aerial environment can have a large impact on the performance of the migrant and is usually highly dynamic, making it beneficial for a bird to regularly check the flight conditions at alternative altitudes. We recorded the migrations between northern Europe and sub-Saharan Africa of European nightjars Caprimulgus europaeus to explore their altitudinal space use during spring and autumn flights and to test whether their climbs and descents were performed according to predictions from flight mechanical theory. Spring migration across all regions was associated with more exploratory vertical flights involving major climbs, a higher degree of vertical displacement within flights, and less time spent in level flight, although flight altitude per se was only higher during the Sahara crossing. The nightjars commonly operated at ascent rates below the theoretical maximum, and periods of descent were commonly undertaken by active flight, and rarely by gliding flight, which has been assumed to be a cheaper locomotion mode during descents. The surprisingly frequent shifts in flight altitude further suggest that nightjars can perform vertical displacements at a relatively low cost, which is expected if the birds can allocate potential energy gained during climbs to thrust forward movement during descents. The results should inspire future studies on the potential costs associated with frequent altitude changes and their trade-offs against anticipated flight condition improvements for aerial migrants.

Oscillations make a self-scaled model for honeybees' visual odometer reliable regardless of flight trajectory

Honeybees foraging and recruiting nest-mates by performing the waggle dance need to be able to gauge the flight distance to the food source regardless of the wind and terrain conditions. Previous authors have hypothesized that the foragers’ visual odometer mathematically integrates the angular velocity of the ground image sweeping backward across their ventral viewfield, known as translational optic flow. The question arises as to how mathematical integration of optic flow (usually expressed in radians/s) can reliably encode distances, regardless of the height and speed of flight. The vertical self-oscillatory movements observed in honeybees trigger expansions and contractions of the optic flow vector field, yielding an additional visual cue called optic flow divergence. We have developed a self-scaled model for the visual odometer in which the translational optic flow is scaled by the visually estimated current clearance from the ground. In simulation, this model, which we have called SOFIa, was found to be reliable in a large range of flight trajectories, terrains and wind conditions. It reduced the statistical dispersion of the estimated flight distances approximately 10-fold in comparison with the mathematically integrated raw optic flow model. The SOFIa model can be directly implemented in robotic applications based on minimalistic visual equipment.

Compensation for wind drift in the nocturnally migrating Song Thrushes in relation to altitude and wind

Compensation for wind drift in relation to the side-wind velocity and altitude was investigated in Song Thrushes during autumn migration. The birds were recorded at night flying above the prominent leading line of a marine spit which coincided with the general direction of their migration. Among the large size passerine species, Song Thrushes were identified by a combination of five flight characteristics typical only of this species during particular periods of autumn. The thrushes showed different reactions to the crosswinds: complete and partial compensation for the displacement and drift. Under normal visibility, the completeness of compensation depended both on the velocity of the side-wind and altitude. The degree of compensation achieved was reduced with an increase of altitude, regardless of the wind. Under the same wind conditions, the angle of drift (the angle between the track direction and the leading line) increased with altitude, but the number of birds that compensated for drift decreased. On average, at heights below 300 m agl, the thrushes were capable of compensating completely for moderate winds; between 300 and 600 m agl compensation was partial; but above 600 m the birds drifted completely. Birds of the same species flying above the same terrain may demonstrate different reactions to the same crosswind depending on altitude. Meanwhile, flight tracks gradually deviated from the leading line with an increase in altitude, the headings of the birds got closer to the general migratory direction. It is more likely that the birds control displacement using the visual flow regulation principle by the angular velocity of the landmarks below them running aside in relation to their flight direction, which is inversely proportional to the altitude. Low flying thrushes promptly reacted to the shifting of the leading line of the spit with an average angular velocity of more than 0.8°/s perpendicular to the direction of flight and compensated completely for drift. Shifting of the leading line with an angular velocity of less than 0.4°/s, the high flying birds did not seem to notice or did not try to compensate for displacement deliberately.