Flight of the dragonflies and damselflies

This work is a synthesis of our current understanding of the mechanics, aerodynamics and visually mediated control of dragonfly and damselfly flight, with the addition of new experimental and computational data in several key areas. These are: the diversity of dragonfly wing morphologies, the aerodynamics of gliding flight, force generation in flapping flight, aerodynamic efficiency, comparative flight performance and pursuit strategies during predatory and territorial flights. New data are set in context by brief reviews covering anatomy at several scales, insect aerodynamics, neuromechanics and behaviour. We achieve a new perspective by means of a diverse range of techniques, including laser-line mapping of wing topographies, computational fluid dynamics simulations of finely detailed wing geometries, quantitative imaging using particle image velocimetry of on-wing and wake flow patterns, classical aerodynamic theory, photography in the field, infrared motion capture and multi-camera optical tracking of free flight trajectories in laboratory environments. Our comprehensive approach enables a novel synthesis of datasets and subfields that integrates many aspects of flight from the neurobiology of the compound eye, through the aeromechanical interface with the surrounding fluid, to flight performance under cruising and higher-energy behavioural modes

DragonDrop: passive dynamics and control strategies of aerial righting in the dragonfly

Dragonflies perform dramatic aerial manoeuvres when hunting prey or chasing rivals but glide leisurely with wings virtually fixed. This makes dragonflies a great system to explore how to minimize the trade-off between manoeuvrability and stability. We challenged the dragonfly by dropping it from selected inverted attitudes and digitised the 6-degrees-of-freedom aerial recovery kinematics via custom motion capture techniques. From these kinematic data we then performed rigid-body inverse dynamics to reconstruct the forces and torques involved in the righting behaviour. We found that inverted dragonflies typically recover themselves with the shortest rotation from the initial body inclination. Additionally, they exhibited a strong tendency to pitch up with their head leading out of the manoeuvre. Surprisingly, anaesthetised dragonflies could also complete the aerial righting. Such passive righting disappears in recently dead dragonflies but can be partially recovered by waxing their wings to mimic the wing posture of the anesthetised dragonflies. Our inverse dynamics model and wind tunnel experiments support the idea that certain wing postures readily provide stability and may explain the dragonfly's rotational preference. This work demonstrates for the first time that aerodynamically stable body configuration exists in gliding insects, and an active insect can leverage this passive stability as needed.The Readme file entitled "Fabian_et_al_DragonDrop_README.txt" is enclosed with the data and should give the relevant information required to access and assess the data.This kinematic data has been collected using 8 motion capture cameras tracking a variable number (generally 5) of markers. Dragonflies were dropped from selected inverted orientations as detailed in the paper itself and a ReadMe file has been provided with the data to facilitate navigation through the many kinematic parameters being measured. All data have gone through extensive processing, however raw captured coordinates are also included within the files

Dragondrop: a novel passive mechanism for aerial righting in the dragonfly

Dragonflies perform dramatic aerial manoeuvres when chasing targets but glide for periods during cruising flights. This makes dragonflies a great system to explore the role of passive stabilizing mechanisms that do not compromise manoeuvrability. We challenged dragonflies by dropping them from selected inverted attitudes and collected 6-degrees-of-freedom aerial recovery kinematics via custom motion capture techniques. From these kinematic data, we performed rigid-body inverse dynamics to reconstruct the forces and torques involved in righting behaviour. We found that inverted dragonflies typically recover themselves with the shortest rotation from the initial body inclination. Additionally, they exhibited a strong tendency to pitch-up with their head leading out of the manoeuvre, despite the lower moment of inertia in the roll axis. Surprisingly, anaesthetized dragonflies could also complete aerial righting reliably. Such passive righting disappeared in recently dead dragonflies but could be partially recovered by waxing their wings to the anaesthetised posture. Our kinematics data, inverse dynamics model and wind-tunnel experiments suggest that the dragonfly's long abdomen and wing posture generate a rotational tendency and passive attitude recovery mechanism during falling. This work demonstrates an aerodynamically stable body configuration in a flying insect and raises new questions in sensorimotor control for small flying systems.</jats:p

Through the eyes of a bird: modelling visually guided obstacle flight

Various flight navigation strategies for birds have been identified 9 at the large spatial scales of migratory and homing behaviors. However, relatively little is known about close range obstacle negotiation through cluttered environments. To examine obstacle flight guidance, we tracked pigeons (C. livea) flying through an artificial forest of vertical poles. Interestingly, pigeons adjusted their flight path only ~1.5m from the forest entry, suggesting a reactive mode of path planning. Combining flight trajectories with obstacle pole positions, we reconstructed the visual experience of the pigeons throughout obstacle flights. Assuming proportional-derivative (PD) control with a constant delay, we searched the relevant parameter space of steering gains and visuomotor delays that best explained the observed steering. We found that a pigeon’s steering resembles proportional control driven by the error angle between the flight direction and the desired opening, or gap, between obstacles. Using this pigeon steering controller, we simulated obstacle flights and showed that pigeons do not simply steer to the nearest opening in the direction of flight or destination. Pigeons bias their flight direction toward larger visual gaps when making fast steering decisions. The proposed behavioral modeling method converts the obstacle avoidance behavior into a (piece-wise) target-aiming behavior, which is better defined and understood. This study demonstrates how such an approach decomposes open-loop free-flight behaviors into components that can be independently evaluated.Organismic and Evolutionary Biolog