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

Impact hazard protection efficiency by a small kinetic impactor

In this paper the ability of a small kinetic impactor spacecraft to mitigate an Earth-threatening asteroid is assessed by means of a novel measure of efficiency. This measure estimates the probability of a space system to deflect a single randomly-generated Earth-impacting object to a safe distance from the Earth. This represents a measure of efficiency that is not biased by the orbital parameters of a test-case object. A vast number of virtual Earth-impacting scenarios are investigated by homogenously distributing in orbital space a grid of 17,518 Earth impacting trajectories. The relative frequency of each trajectory is estimated by means Opik’s theory and Bottke’s near Earth objects model. A design of the entire mitigation mission is performed and the largest deflected asteroid computed for each impacting trajectory. The minimum detectable asteroid can also be estimated by an asteroid survey model. The results show that current technology would likely suffice against discovered airburst and local damage threats, whereas larger space systems would be necessary to reliably tackle impact hazard from larger threats. For example, it is shown that only 1,000 kg kinetic impactor would suffice to mitigate the impact threat of 27.1% of objects posing similar threat than that posed by Apophis

Paradoxical popups: Why are they hard to catch?

Even professional baseball players occasionally find it difficult to gracefully approach seemingly routine pop-ups. This paper describes a set of towering pop-ups with trajectories that exhibit cusps and loops near the apex. For a normal fly ball, the horizontal velocity is continuously decreasing due to drag caused by air resistance. But for pop-ups, the Magnus force (the force due to the ball spinning in a moving airflow) is larger than the drag force. In these cases the horizontal velocity decreases in the beginning, like a normal fly ball, but after the apex, the Magnus force accelerates the horizontal motion. We refer to this class of pop-ups as paradoxical because they appear to misinform the typically robust optical control strategies used by fielders and lead to systematic vacillation in running paths, especially when a trajectory terminates near the fielder. In short, some of the dancing around when infielders pursue pop-ups can be well explained as a combination of bizarre trajectories and misguidance by the normally reliable optical control strategy, rather than apparent fielder error. Former major league infielders confirm that our model agrees with their experiences.Comment: 28 pages, 10 figures, sumitted to American Journal of Physic

A Neural Model of Visually Guided Steering, Obstacle Avoidance, and Route Selection

A neural model is developed to explain how humans can approach a goal object on foot while steering around obstacles to avoid collisions in a cluttered environment. The model uses optic flow from a 3D virtual reality environment to determine the position of objects based on motion discotinuities, and computes heading direction, or the direction of self-motion, from global optic flow. The cortical representation of heading interacts with the representations of a goal and obstacles such that the goal acts as an attractor of heading, while obstacles act as repellers. In addition the model maintains fixation on the goal object by generating smooth pursuit eye movements. Eye rotations can distort the optic flow field, complicating heading perception, and the model uses extraretinal signals to correct for this distortion and accurately represent heading. The model explains how motion processing mechanisms in cortical areas MT, MST, and VIP can be used to guide steering. The model quantitatively simulates human psychophysical data about visually-guided steering, obstacle avoidance, and route selection.Air Force Office of Scientific Research (F4960-01-1-0397); National Geospatial-Intelligence Agency (NMA201-01-1-2016); National Science Foundation (NSF SBE-0354378); Office of Naval Research (N00014-01-1-0624

A 5-kW xenon ion thruster lifetest

The results of the first life test of a high power ring-cusp ion thruster are presented. A 30-cm laboratory model thruster was operated steady-state at a nominal beam power of 5 kW on xenon propellant for approximately 900 hours. This test was conducted to identify life-timing erosion modifications, and to demonstrate operation using simplified power processing. The results from this test are described including the conclusions derived from extensive post-test analyses of the thruster. Modifications to the thruster and ground support equipment, which were incorporated to solve problems identified by the lifetest, are also described

Postural adjustments in catching: on the interplay between segment stabilization and equilibrium control

The purpose of this study was to investigate postural adjustments in one-handed ball catching. Specifically, the functional role of anticipatory postural adjustments (APA) during the initial arm raising and subsequent postural adjustments (SPA) for equilibrium control and ball-hand impact were scrutinized. Full-body kinematics and kinetics allowed an analysis of the mechanical consequences of raising up the arm and preparing for ball-hand impact. APA for catching were suggested to be for segment stabilization. SPA had a functional role for equilibrium control by an inverted pendulum mechanism but were also involved in preparing for the impact of the ball on the hand, which was illustrated by an increased postural response at the end of the movement. These results were compared with raising up the arm in a well-studied reaction-time task, for which an additional counter rotation equilibrium mechanism was observed. Together, our findings demonstrate that postural adjustments should be investigated in relation to their specific functional task constraints, rather than generalizing the functional role of these postural adjustments over different tasks

A Neural Model of Visually Guided Steering, Obstacle Avoidance, and Route Selection

A neural model is developed to explain how humans can approach a goal object on foot while steering around obstacles to avoid collisions in a cluttered environment. The model uses optic flow from a 3D virtual reality environment to determine the position of objects based on motion discontinuities, and computes heading direction, or the direction of self-motion, from global optic flow. The cortical representation of heading interacts with the representations of a goal and obstacles such that the goal acts as an attractor of heading, while obstacles act as repellers. In addition the model maintains fixation on the goal object by generating smooth pursuit eye movements. Eye rotations can distort the optic flow field, complicating heading perception, and the model uses extraretinal signals to correct for this distortion and accurately represent heading. The model explains how motion processing mechanisms in cortical areas MT, MST, and posterior parietal cortex can be used to guide steering. The model quantitatively simulates human psychophysical data about visually-guided steering, obstacle avoidance, and route selection.Air Force Office of Scientific Research (F4960-01-1-0397); National Geospatial-Intelligence Agency (NMA201-01-1-2016); National Science Foundation (SBE-0354378); Office of Naval Research (N00014-01-1-0624

Effect of branch position and light availability on shoot growth of understory sugar maple and yellow birch saplings

Phenotypic plasticity enables tree saplings to change their morphology according to their environment to grow toward a better light micro-habitat. Therefore, processes of crown development could be expected to vary as a function of light. The objectives of this study were to (i) evaluate the effects of position and light availability on shoot growth within the crowns of understory saplings of sugar maple (Acer saccharum Marsh.) and yellow birch (Betula alleghaniensis Britton.); (ii) develop a new vigour index for shoots; and (iii) evaluate the possible factors relating to branch mortality in the crown of sugar maple saplings. The results revealed that there is a clear branch position effect on shoot growth in the crown for yellow birch saplings and that it is partly related to the presence of two types of shoots. Dead branches were located at the bottom of the crown of sugar maple saplings; they were smaller in size, had wider angles and had lower indexes of vigour than live branches found nearby. Preliminary results obtained on the vigour index indicate that it is a potentially useful tool for predicting the growth and vigour status of a branch

A layered fuzzy logic controller for nonholonomic car-like robot

A system for real time navigation of a nonholonomic car-like robot in a dynamic environment consists of two layers is described: a Sugeno-type fuzzy motion planner; and a modified proportional navigation based fuzzy controller. The system philosophy is inspired by human routing when moving between obstacles based on visual information including right and left views to identify the next step to the goal. A Sugeno-type fuzzy motion planner of four inputs one output is introduced to give a clear direction to the robot controller. The second stage is a modified proportional navigation based fuzzy controller based on the proportional navigation guidance law and able to optimize the robot's behavior in real time, i.e. to avoid stationary and moving obstacles in its local environment obeying kinematics constraints. The system has an intelligent combination of two behaviors to cope with obstacle avoidance as well as approaching a target using a proportional navigation path. The system was simulated and tested on different environments with various obstacle distributions. The simulation reveals that the system gives good results for various simple environments