scholarly journals An insect-inspired collapsible wing hinge dampens collision-induced body rotation rates in a microrobot

2019 ◽  
Vol 16 (150) ◽  
pp. 20180618 ◽  
Author(s):  
Andrew M. Mountcastle ◽  
E. Farrell Helbling ◽  
Robert J. Wood
Keyword(s):  
Flight Control ◽  
Real World ◽  
Micro Air Vehicles ◽  
Body Rotation ◽  
Rotation Rates ◽  
Flying Insects ◽  
Wing Damage ◽  
Wing Wear ◽  
Wing Tip ◽  
Wing Stroke

Some flying insects frequently collide their wingtips with obstacles, and the next generation of insect-inspired micro air vehicles will inevitably face similar wing collision risks when they are deployed in real-world environments. Wasp wings feature a flexible resilin joint called a ‘costal break’ that allows the wingtip to reversibly collapse upon collision, helping to mitigate wing damage over repeated collisions. However, the costal break may provide additional benefits beyond reducing wing wear. We tested the hypothesis that a collapsible wing tip can also dampen sudden and unpredictable body rotations caused by collisions. We designed a wing buckle hinge for an insect-scale microrobot, inspired by the costal break in wasp wings, and performed wing collision tests in a yaw-based magnetic tether system. We found that a collapsible wing tip reduced collision-induced airframe yaw rates by approximately 40% compared to a stiff wing, and that the effect was most pronounced for collisions that occurred early in the wing stroke. Our results suggest that a collapsible wingtip may simplify flight control requirements in both insects and insect-scale microrobots. We also introduce a scalable hinge design for engineering applications that recreates the nonlinear strain-weakening behaviour of a costal break.

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

2021 ◽  
Author(s):  
Alison I. Weber ◽  
Thomas L. Daniel ◽  
Bingni W. Brunton
Keyword(s):  
Flight Control ◽  
Insect Flight ◽  
Body Rotation ◽  
Neural Encoding ◽  
Single Action ◽  
Wing Model ◽  
Flying Insects ◽  
Small Set ◽  
Wing Structure ◽  
And Performance

AbstractAnimals rely on sensory feedback to generate accurate, reliable movements. In many flying insects, strain-sensitive neurons on the wings provide rapid feedback that enables stable flight control. While the impacts of wing structure on aerodynamic performance have been widely studied, the impacts of wing structure on sensing remain 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 over a flapping wing to detect body rotation about different axes, using a computational wing model with varying flexural stiffness inspired by the hawkmoth Manduca sexta. A small set of mechanosensors, conveying strain information at key locations with a single action potential per wingbeat, permit 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 their joint evolution.

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

2021 ◽  
Vol 17 (8) ◽  
pp. e1009195
Author(s):  
Alison I. Weber ◽  
Thomas L. Daniel ◽  
Bingni W. Brunton
Keyword(s):  
Flight Control ◽  
Insect Flight ◽  
Body Rotation ◽  
Neural Encoding ◽  
Single Action ◽  
Wing Model ◽  
Flying Insects ◽  
Small Set ◽  
Wing Structure ◽  
And Performance

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.

scholarly journals Spatial odor discrimination in hawkmoth, Manduca sexta (L.)

2020 ◽  
Author(s):  
P. Kalyanasundaram ◽  
M. A. Willis
Keyword(s):  
Spatial Distribution ◽  
Manduca Sexta ◽  
Flight Control ◽  
Spatial Information ◽  
Egg Laying ◽  
Proboscis Extension Reflex ◽  
Flying Insects ◽  
Odor Learning ◽  
Odor Plumes ◽  
Proboscis Extension

AbstractFlying insects track turbulent odor plumes to find mates, food and egg-laying sites. To maintain contact with the plume, insects are thought to adapt their flight control according to the distribution of odor in the plume using the timing of odor onsets and intervals between odor encounters. Although timing cues are important, few studies have addressed whether insects are capable of deriving spatial information about odor distribution from bilateral comparisons between their antennae in flight. The proboscis extension reflex (PER) associative learning protocol, originally developed to study odor learning in honeybees, was modified to show hawkmoths, Manduca sexta, can discriminate between odor stimuli arriving on either antenna. We show moths discriminated the odor arrival side with an accuracy of >70%. The information about spatial distribution of odor stimuli is thus available to moths searching for odor sources, opening the possibility that they use both spatial and temporal odor information.

scholarly journals Rules to fly by: pigeons navigating horizontal obstacles limit steering by selecting gaps most aligned to their flight direction

2017 ◽  
Vol 7 (1) ◽  
pp. 20160093 ◽  
Author(s):  
Ivo G. Ros ◽  
Partha S. Bhagavatula ◽  
Huai-Ti Lin ◽  
Andrew A. Biewener
Keyword(s):  
Flight Control ◽  
Three Dimensional ◽  
Obstacle Detection ◽  
Head Movements ◽  
Flight Mechanics ◽  
Unmanned Aerial Systems ◽  
Natural Environments ◽  
Motion Vision ◽  
Flight Direction ◽  
Wing Stroke

Flying animals must successfully contend with obstacles in their natural environments. Inspired by the robust manoeuvring abilities of flying animals, unmanned aerial systems are being developed and tested to improve flight control through cluttered environments. We previously examined steering strategies that pigeons adopt to fly through an array of vertical obstacles (VOs). Modelling VO flight guidance revealed that pigeons steer towards larger visual gaps when making fast steering decisions. In the present experiments, we recorded three-dimensional flight kinematics of pigeons as they flew through randomized arrays of horizontal obstacles (HOs). We found that pigeons still decelerated upon approach but flew faster through a denser array of HOs compared with the VO array previously tested. Pigeons exhibited limited steering and chose gaps between obstacles most aligned to their immediate flight direction, in contrast to VO navigation that favoured widest gap steering. In addition, pigeons navigated past the HOs with more variable and decreased wing stroke span and adjusted their wing stroke plane to reduce contact with the obstacles. Variability in wing extension, stroke plane and wing stroke path was greater during HO flight. Pigeons also exhibited pronounced head movements when negotiating HOs, which potentially serve a visual function. These head-bobbing-like movements were most pronounced in the horizontal (flight direction) and vertical directions, consistent with engaging motion vision mechanisms for obstacle detection. These results show that pigeons exhibit a keen kinesthetic sense of their body and wings in relation to obstacles. Together with aerodynamic flapping flight mechanics that favours vertical manoeuvring, pigeons are able to navigate HOs using simple rules, with remarkable success.

Four-Rotor Autonomous Vehicle

2014 ◽  
Vol 505-506 ◽  
pp. 286-291
Author(s):  
Shu Yun Wu ◽  
Xu Hao Lv
Keyword(s):  
Flight Control ◽  
Autonomous Vehicle ◽  
Computer Control ◽  
Control Unit ◽  
Micro Air Vehicles ◽  
Motor Speed ◽  
Single Chip ◽  
Flight Mode ◽  
Reliable Performance ◽  
Control Flight

Four rotary-wing micro air vehicles use four motors as the power unit, by adjusting the motor speed control flight of underactuated systems [. In order to achieve four-rotor autonomous vehicle autonomous flight control, preliminary design of flight control system, and use F5F100LEA single-chip as computer control unit, Proposed the flight system hardware design. Vehicle has the advantages of light weight, small size, low power consumption. After several laboratory tests, the design and reliable performance, to meet the aircraft take off, hover, landing flight mode control requirements.

scholarly journals Insect-like flapping wing mechanism based on a double spherical Scotch yoke

2005 ◽  
Vol 2 (3) ◽  
pp. 223-235 ◽  
Author(s):  
Cezary Galiński ◽  
Rafał Żbikowski
Keyword(s):  
Insect Flight ◽  
Micro Air Vehicles ◽  
Flapping Wing ◽  
Controlled Study ◽  
Concept Design ◽  
Test Bed ◽  
Insect Wing ◽  
Flying Insects ◽  
Adjustable Mechanism ◽  
Air Vehicles

We describe the rationale, concept, design and implementation of a fixed-motion (non-adjustable) mechanism for insect-like flapping wing micro air vehicles in hover, inspired by two-winged flies (Diptera). This spatial (as opposed to planar) mechanism is based on the novel idea of a double spherical Scotch yoke. The mechanism was constructed for two main purposes: (i) as a test bed for aeromechanical research on hover in flapping flight, and (ii) as a precursor design for a future flapping wing micro air vehicle. Insects fly by oscillating (plunging) and rotating (pitching) their wings through large angles, while sweeping them forwards and backwards. During this motion the wing tip approximately traces a ‘figure-of-eight’ or a ‘banana’ and the wing changes the angle of attack (pitching) significantly. The kinematic and aerodynamic data from free-flying insects are sparse and uncertain, and it is not clear what aerodynamic consequences different wing motions have. Since acquiring the necessary kinematic and dynamic data from biological experiments remains a challenge, a synthetic, controlled study of insect-like flapping is not only of engineering value, but also of biological relevance. Micro air vehicles are defined as flying vehicles approximately 150 mm in size (hand-held), weighing 50–100 g, and are developed to reconnoitre in confined spaces (inside buildings, tunnels, etc.). For this application, insect-like flapping wings are an attractive solution and hence the need to realize the functionality of insect flight by engineering means. Since the semi-span of the insect wing is constant, the kinematics are spatial; in fact, an approximate figure-of-eight/banana is traced on a sphere. Hence a natural mechanism implementing such kinematics should be (i) spherical and (ii) generate mathematically convenient curves expressing the figure-of-eight/banana shape. The double spherical Scotch yoke design has property (i) by definition and achieves (ii) by tracing spherical Lissajous curves.

scholarly journals Dynamics of Micro-Air-Vehicle with Flapping Wings

10.14311/526 ◽  
2004 ◽  
Vol 44 (2) ◽  
Author(s):  
K. Sibilski
Keyword(s):  
Flight Control ◽  
Computational Models ◽  
Inertial Sensors ◽  
Early Stage ◽  
Micro Air Vehicles ◽  
The Body ◽  
Flapping Wings ◽  
Control Algorithms ◽  
Micromechanical Flying Insect ◽  
And Performance

Small (approximately 6 inch long, or hand-held) reconnaissance micro air vehicles (MAVs) will fly inside buildings, and require hover for observation, and agility at low speeds to move in confined spaces. For this flight envelope insect-like flapping wings seem to be an optimal mode of flying. Investigation of the aerodynamics of flapping wing MAVs is very challenging. The problem involves complex unsteady, viscous flow (mainly laminar), with the moving wing generating vortices and interacting with them. At this early stage of research only a preliminary insight into the nature of the little known aerodynamics of MAVs has been obtained. This paper describes computational models for simulation of the controlled motion of a microelectromechanical flying insect – entomopter. The design of software simulation for entomopter flight (SSEF) is presented. In particular, we will estimate the flight control algorithms and performance for a Micromechanical Flying Insect (MFI), a 80–100 mm (wingtip-to-wingtip) device capable of sustained autonomous flight. The SSEF is an end-to-end tool composed of several modular blocks which model the wing aerodynamics and dynamics, the body dynamics, and in the future, the environment perception, control algorithms, the actuators dynamics, and the visual and inertial sensors. We present the current state of the art of its implementation, and preliminary results. 

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