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At least 181 records · Page 10

Building wakes in disturbed layers

The wind profiles in the wakes of buildings in a disturbed shear layer are investigated for conditions experienced during aircraft take-off and landing. Experiments were conducted in a pipe flow apparatus in which an equilibrium flow is disturbed by pipe roughness, simulating obstacles upwind of a building, with the disturbed flow made to flow past a second obstacle, simulating a building. Velocity and turbulence profiles of disturbed and equilibrium flows upstream and downstream of the obstacles are presented. It is concluded that the integrated momentum flow of a boundary layer behind an obstacle can be greater than the upstream momentum flow, if the exponent of the upstream velocity profile is sufficiently high and the boundary layer has been disturbed by upstream obstacles. The rise of the turbulence level behind the obstacle is also dependent on the profile exponent in a disturbed layer.

Logan, E.↗

Spacecraft-environment interaction: The environmental plasma aspect

The effects involved in the interaction between an obstacle and a space plasma can be divided into: (1) effects on the obstacle itselt (i.e., its charging); and (2) effects on the environmental plasma due to the motion of the obstacle (i.e., the creation of shocks ahead of the obstacle and complicated wakes behind the obstacle). In the wake (or antisolar direction), plasma oscillations are excited and instabilities, wave-particle interactions, turbulence, etc., are believed to take place. The effects on the obstacle and on the environmental space plasma are coupled. Hence, simultaneous solutions to the Vlasov (or Boltzmann) and Poisson equations are sought. To obtain realistic solutions of practical use, three-dimensional and time-dependent models of the interaction are needed. Achieving the latter is indeed not simple.

Samir, U.↗

Mixing and Noise Benefit Versus Thrust Penalty in Supersonic Jets Using Impingement Tones

This paper reports the results of an experimental investigation on the effect of impingement tones generated by obstacles of various geometries on the spreading of a supersonic jet flow. A rectangular supersonic jet was produced using a convergent-divergent nozzle that was operated near its design point (with shocks minimized). The immersion of obstacles in the flow produced an intense impingement tone which then propagated upstream (as feedback) to the jet lip and excited the antisymmetric hydrodynamic mode in the jet, thus setting up a resonant self-sustaining loop. The violent flapping motion of the jet due to excitation of the antisymmetric mode, combined with the unsteady wakes of the obstacles, produced large changes in jet mixing. It was possible to control the frequency and amplitude of the impingement tone excitation by varying the nozzle-to-obstacle distance and the obstacle immersion. By proper shaping of the obstacles it was possible to reduce the thrust penalty significantly.

Raman, Ganesh↗

Small UAV Flight Planning in Urban Environments

This work proposes a fast algorithm for generating obstacle-free and wind-efficient flight paths at a constant above-ground-level altitude in urban environments because a fast flight path planning algorithm is an essential function or service needed for enabling small unmanned aerial vehicle (sUAV) to operate in urban environments within Class G airspace. The proposed method first converts the 3D path planning problem to a 2D problem by constructing an obstacle map at a given above-ground-level altitude. A quad-tree decomposition is then used to build a search space in terms of obstacle occupancy and wind difference. The wind cost of traveling through each cell is defined based on energy consumption under various wind conditions. A repulsive potential is also adopted to make sure that the flight plans stay away from obstacles. The Theta* search algorithm, a variant of A* algorithm, is applied to mitigate the path angle change constraints introduced by grid-based graphs. With the Theta* and postsmoothing techniques, an obstacle-free, wind efficient, and constant above-ground-level flight plan can be quickly generated for sUAV operations in urban environments while meeting the lateral path angle constraints. The results showed that the path planning algorithm is efficient and can be finished within several seconds. With a proper choice of wind coefficient, the proposed path planning algorithm outperforms the multiple-shooting trajectory optimization method even in an obstacle-free environment. With the flexibility of incorporating other geo-related costs and computation efficiency, the proposed algorithm shows the potential for real-time flight path planning in complex urban environments.

Path planning↗

Computer vision techniques for rotorcraft low-altitude flight

A description is given of research that applies techniques from computer vision to automation of rotorcraft navigation. The effort emphasizes the development of a methodology for detecting the ranges to obstacles in the region of interest based on the maximum utilization of passive sensors. The range map derived from the obstacle detection approach can be used as obstacle data for the obstacle avoidance in an automataic guidance system and as advisory display to the pilot. The lack of suitable flight imagery data, however, presents a problem in the verification of concepts for obstacle detection. This problem is being addressed by the development of an adequate flight database and by preprocessing of currently available flight imagery. Some comments are made on future work and how research in this area relates to the guidance of other autonomous vehicles.

Sridhar, Banavar↗

Teleautonomous guidance for mobile robots

Teleautonomous guidance (TG), a technique for the remote guidance of fast mobile robots, has been developed and implemented. With TG, the mobile robot follows the general direction prescribed by an operator. However, if the robot encounters an obstacle, it autonomously avoids collision with that obstacle while trying to match the prescribed direction as closely as possible. This type of shared control is completely transparent and transfers control between teleoperation and autonomous obstacle avoidance gradually. TG allows the operator to steer vehicles and robots at high speeds and in cluttered environments, even without visual contact. TG is based on the virtual force field (VFF) method, which was developed earlier for autonomous obstacle avoidance. The VFF method is especially suited to the accommodation of inaccurate sensor data (such as that produced by ultrasonic sensors) and sensor fusion, and allows the mobile robot to travel quickly without stopping for obstacles.

Borenstein, J.↗

Technologies for automating rotorcraft nap-of-the-earth flight

This paper discusses the technologies required for automating rotorcraft nap-of-the-earth flight, where the use of natural obstacles for masking from the enemy is intentional and the danger of undesirable obstacles such as enemy traps is real. Specifically, the automatic guidance structure is modeled by three decision-making levels: the far-field mission planning and the mid-field terrain-masking trajectory shaping are both driven by prestored terrain data, whereas the nearfield obstacle detection/avoidance is driven by real-time on-board sensor data. This paper summarizes the far-field and mid-field accomplishments, and reports on the status of the more-recent efforts in obstacle detection and avoidance development. Obstacle detection is based primarily on passive imaging sensors for the desirable properties of covertness and wide field of view, although active sensors are included in the structure to provide the much needed high resolution for thin-wire detection.

Cheng, Victor H. L.↗

Neural network structure for navigation using potential fields

A hybrid-network method for obstacle avoidance in the truck-backing system of D. Nguyen and B. Widrow (1989) is presented. A neural network technique for vehicle navigation and control in the presence of obstacles has been developed. A potential function which peaks at the surface of obstacles and has its minimum at the proper vehicle destination is computed using a network structure. The field is guaranteed not to have spurious local minima and does not have the property of flattening-out far from the goal. A feedforward neural network is used to control the steering of the vehicle using local field information. The network is trained in an obstacle-free space to follow the negative gradient of the field, after which the network is able to control and navigate the truck to its target destination in a space of obstacles which may be stationary or movable.

Plumer, Edward S.↗

The Transition Phase in the Take-Off of an Airplane, Special Report

An investigation was undertaken to determine the character and importance of the transition phase between the ground run and steady climb in the takeoff of an airplane and the effects of various factors on this phase and on the airborne part of the takeoff as a whole. The information was obtained from a series of step-by-step integrations, which defined the motion of the airplane during the transition and which were based on data derived from actual takeoff tests of a Verville AT airplane. Both normal and zoom takeoffs under several loading and takeoff speed conditions were considered. The effects of a moderate wind with a corresponding wind gradient and the effect of proximity of the ground were also investigated. The results show that, for normal takeoffs, the best transition was realized at the lowest possible takeoff speed. Moreover, this speed gave the shortest overall takeoff distance for normal takeoffs. Zoom takeoffs required a shorter overall takeoff run than normal takeoffs, particularly with a heavy landing, if the obstacle to be cleared was sufficiently high (greater than 50 feet); no advantage was indicated to the airplane with a light loading if the height to be cleared was less. The error resulting from the neglect of the transition in the calculation of the airborne distance of takeoff was found to vary from 4% with the heaviest loading considered to -4% with the lightest loading for normal takeoffs over a 100-ft obstacle; the percentage error was twice as great for a 50-foot obstacle. For zoom takeoffs the error attained much greater values. The average wind gradient corresponding to a 5-mile-per-hour surface wind reduced the airborne distance required to clear a 50-foot obstacle by about 9% with the lightest loading and 16% with the heaviest loading; for both cases. The overall reduction due to this wind was approximately twice that resulting from the wind gradient alone. A simple expression for the reduction of observed takeoff performance to no-wind conditions is presented. Ground effect is shown to reduce the airborne distance to attain a height of 50 foot by 10% with the lightest loading and 16% with the heaviest loading; for a 100-foot obstacle the percentage reduction was about 1/2 as great.

Wetmore, J. W.↗

Improved Path Planning Onboard the Mars Exploration Rovers

A revised version of the AutoNav (autonomous navigation with hazard avoidance) software running onboard each Mars Exploration Rover (MER) affords better obstacle avoidance than does the previous version. Both versions include GESTALT (Grid-based Estimation of Surface Traversability Applied to Local Terrain), a navigation program that generates local-terrain models from stereoscopic image pairs captured by onboard rover cameras; uses this information to evaluate candidate arcs that extend across the terrain from the current rover location; ranks the arcs with respect to hazard avoidance, minimization of steering time, and the direction towards the goal; and combines the rankings in a weighted vote to select an arc, along which the rover is then driven. GESTALT works well in navigating around small isolated obstacles, but tends to fail when the goal is on the other side of a large obstacle or multiple closely spaced small obstacles. When that occurs, the goal seeking votes and hazard avoidance votes conflict severely. The hazard avoidance votes will not allow the rover to drive through the unsafe area, and the waypoint votes will not allow enough deviation from the straight-line path for the rover to get around the hazard. The rover becomes stuck and is unable to reach the goal. The revised version of AutoNav utilizes a global path-planning program, Field D*, to evaluate the cost of traveling from the end of each GESTALT arc to the goal. In the voting process, Field D* arc votes supplant GESTALT goal-seeking arc votes. Hazard avoidance, steering bias, and Field D* votes are merged and the rover is driven a preset distance along the arc with the highest vote. Then new images are acquired and the process as described is repeated until the goal is reached. This new technology allows the rovers to autonomously navigate around much more complex obstacle arrangements than was previously possible. In addition, this improved autonomy enables longer traverses per Sol (a day on Mars), and can make planning drives easier for operators on Earth.

Stentz, Anthony↗

UAV Inspection of Electrical Transmission Infrastructure with Path Conformance Autonomy and Lidar-Based Geofences NASA Report on UTM Reference Mission Flights at Southern Company Flights November 2016

Flights at low altitudes in close proximity to electrical transmission infrastructure present serious navigational challenges: GPS and radio communication quality is variable and yet tight position control is needed to measure defects while avoiding collisions with ground structures. To advance unmanned aerial vehicle (UAV) navigation technology while accomplishing a task with economic and societal benefit, a high voltage electrical infrastructure inspection reference mission was designed. An integrated air-ground platform was developed for this mission and tested in two days of experimental flights to determine whether navigational augmentation was needed to successfully conduct a controlled inspection experiment. The airborne component of the platform was a multirotor UAV built from commercial off-the-shelf hardware and software, and the ground component was a commercial laptop running open source software. A compact ultraviolet sensor mounted on the UAV can locate 'hot spots' (potential failure points in the electric grid), so long as the UAV flight path adequately samples the airspace near the power grid structures. To improve navigation, the platform was supplemented with two navigation technologies: lidar-to-polyhedron preflight processing for obstacle demarcation and inspection distance planning, and trajectory management software to enforce inspection standoff distance. Both navigation technologies were essential to obtaining useful results from the hot spot sensor in this obstacle-rich, low-altitude airspace. Because the electrical grid extends into crowded airspaces, the UAV position was tracked with NASA unmanned aerial system traffic management (UTM) technology. The following results were obtained: (1) Inspection of high-voltage electrical transmission infrastructure to locate 'hot spots' of ultraviolet emission requires navigation methods that are not broadly available and are not needed at higher altitude flights above ground structures. (2) The sensing capability of a novel airborne UV detector was verified with a standard ground-based instrument. Flights with this sensor showed that UAV measurement operations and recording methods are viable. With improved sensor range, UAVs equipped with compact UV sensors could serve as the detection elements in a self-diagnosing power grid. (3) Simplification of rich lidar maps to polyhedral obstacle maps reduces data volume by orders of magnitude, so that computation with the resultant maps in real time is possible. This enables real-time obstacle avoidance autonomy. Stable navigation may be feasible in the GPS-deprived environment near transmission lines by a UAV that senses ground structures and compares them to these simplified maps. (4) A new, formally verified path conformance software system that runs onboard a UAV was demonstrated in flight for the first time. It successfully maneuvered the aircraft after a sudden lateral perturbation that models a gust of wind, and processed lidar-derived polyhedral obstacle maps in real time. (5) Tracking of the UAV in the national airspace using the NASA UTM technology was a key safety component of this reference mission, since the flights were conducted beneath the landing approach to a heavily used runway. Comparison to autopilot tracking showed that UTM tracking accurately records the UAV position throughout the flight path.

Moore, Andrew J.↗

Distributed Spatiotemporal Motion Planning for Spacecraft Swarms in Cluttered Environments

This paper focuses on trajectory planning for spacecraft swarms in cluttered environments, like debris fields or the asteroid belt. Our objective is to reconfigure the spacecraft swarm to a desired formation in a distributed manner while minimizing fuel and avoiding collisions among themselves and with obstacles. In our prior work we proposed a novel distributed guidance algorithm for spacecraft swarms in static environments. In this paper, we present the Multi-Agent Moving-Obstacles Spherical Expansion and Sequential Convex Programming (MAMO SE-SCP) algorithm that extends our prior work to include spatiotemporal constraints such as time-varying, moving obstacles and desired time-varying terminal positions. In the MAMO SE-SCP algorithm, each agent uses a spherical-expansion-based sampling algorithm to cooperatively explore the time-varying environment, a distributed assignment algorithm to agree on the terminal position for each agent, and a sequential-convex-programming-based optimization step to compute the locally-optimal trajectories from the current location to the assigned time-varying terminal position while avoiding collision with other agents and moving obstacles. Simulation results demonstrate that the proposed distributed algorithm can be used by a spacecraft swarm to achieve a time-varying, desired formation around an object of interest in a dynamic environment with many moving and tumbling obstacles.

Bandyopadhyay, Saptarshi↗

Distributed Spatiotemporal Motion Planning for Spacecraft Swarms in Cluttered Environments

This paper focuses on trajectory planning for spacecraft swarms in cluttered environments, like debris fields or the asteroid belt. Our objective is to reconfigure the spacecraft swarm to a desired formation in a distributed manner while minimizing fuel and avoiding collisions among themselves and with the obstacles. In our prior work we proposed a novel distributed guidance algorithm for spacecraft swarms in static environments.1 In this paper, we present the Multi-Agent Moving-Obstacles Spherical Expansion and Sequential Convex Programming (MAMO SE–SCP) algorithm that extends our prior work to include spatiotemporal constraints such as time-varying, moving obstacles and desired time-varying terminal positions. In the MAMO SE–SCP algorithm, each agent uses a spherical-expansion-based sampling algorithm to cooperatively explore the time-varying environment, a distributed assignment algorithm to agree on the terminal position for each agent, and a sequential-convex-programming-based optimization step to compute the locally-optimal trajectories from the current location to the assigned time-varying terminal position while avoiding collision with other agent and the moving obstacles. Simulations results demonstrate that the proposed distributed algorithm can be used by a spacecraft swarm to achieve a time-varying, desired formation around an object of interest in a dynamic environment with many moving and tumbling obstacles.

Hadaegh, Fred Y.↗

Validation of A Sensorimotor Disorientation Ground Analog

INTRODUCTION Simulating the sensorimotor disorientation effects of gravity transitions after prolonged stays in microgravity is exceedingly challenging on Earth. In a previous study [1], a Sensorimotor Disorientation Analog (SDA) was developed based on subjective feedback from previously flown astronauts. The purpose of this study was to validate this SDA by comparing performance in movement tasks that have a wealth of spaceflight data against task performance while using the SDA. METHODS Thirty healthy non-astronaut subjects (17 males, 13 females; Mean ± SD, Age: 33.5 ± 7.2 years, Height: 68.0 ± 3.4 in, Weight: 164 ± 26 lbs.) volunteered to participate in this study. Subjects performed three movement tasks: computerized dynamic posturography (CDP), obstacle walk, and tandem walk. For CDP, subjects maintained an upright stance for 20s with eyes closed on an unstable pitch sway-referenced platform with head erect (sensory organization test (SOT)-5) and with head pitch ±20° to an auditory cue(SOT-5M). The obstacle walk involved a sit-to-stand with 10s of quiet stance followed by walking to and around a cone placed 4m away while navigating a 30cm obstacle to the cone and back. The tandem walk involved walking heel-to-toe for approximately 10-12 steps with eyes open and eyes closed. Subjects performed the three movement tasks under three levels of the SDA replicating different time points of recovery: none (preflight), low (Return (R)+24- 48hours), and high (R+0- 24hours). The SDA included galvanic vestibular stimulation (GVS) to disorient the vestibular system and a weighted suit (trunk, wrists, and ankles) to alter proprioceptive feedback and replicate subjective heaviness. RESULTS As the SDA magnitude increased, overall performance outcomes decreased. However, the ability of the SDA to replicate the range of astronaut postflight performance was task dependent. CDP SOT-5 performance across SDA levels closely replicated astronaut performance at all time points. SOT-5M, however, had minimal performance changes across SDA levels and was unable to replicate astronaut performance. The obstacle walk showed performance changes across SDA levels and matched astronaut performance preflight and at R+24-48hrs (low). Obstacle walk performance at the high SDA level was reduced in comparison to the low level; however, it was not replicative of astronaut performance immediately after landing. Last, tandem walk had distinct groupings of performance across SDA levels and was able to elicit a high level of disorientation consistent with R+0-24 hours (high) postflight performance for eyes open and eyes closed. The low SDA level for both eyes open and eyes closed was more disruptive than previous crewmember performance at the R+24-48 hours timepoint. CONCLUSION The SDA was developed to replicate postflight sensorimotor disruptions. However, it is well-known that immediately post-landing, astronauts can experience motion sickness, dehydration, fatigue, orthostatic intolerance, illusory sensations, lumbar pain, etc. This multi-system response to return to 1G varies widely across astronauts and, as such, it was not unexpected that the extreme ends of responses in the R+0-24hrs time period were the most difficult to replicate. These results suggest that the SDA levels are able to elicit distinct performance groupings and, although not able to perfectly replicate R+0-24hrs, the SDA did replicate a large range of performance after return to Earth.

S C Moudy↗

Numerical calculations of velocity and pressure distribution around oscillating airfoils

An analytical procedure based on the Navier-Stokes equations was developed for analyzing and representing properties of unsteady viscous flow around oscillating obstacles. A variational formulation of the vorticity transport equation was discretized in finite element form and integrated numerically. At each time step of the numerical integration, the velocity field around the obstacle was determined for the instantaneous vorticity distribution from the finite element solution of Poisson's equation. The time-dependent boundary conditions around the oscillating obstacle were introduced as external constraints, using the Lagrangian Multiplier Technique, at each time step of the numerical integration. The procedure was then applied for determining pressures around obstacles oscillating in unsteady flow. The obtained results for a cylinder and an airfoil were illustrated in the form of streamlines and vorticity and pressure distributions.

Bratanow, T.↗

Computer simulation and evaluation of edge detection algorithms and their application to automatic path selection

The construction of an autonomous roving vehicle requires the development of complex data-acquisition and processing systems, which determine the path along which the vehicle travels. Thus, a vehicle must possess algorithms which can (1) reliably detect obstacles by processing sensor data, (2) maintain a constantly updated model of its surroundings, and (3) direct its immediate actions to further a long range plan. The first function consisted of obstacle recognition. Obstacles may be identified by the use of edge detection techniques. Therefore, the Kalman Filter was implemented as part of a large scale computer simulation of the Mars Rover. The second function consisted of modeling the environment. The obstacle must be reconstructed from its edges, and the vast amount of data must be organized in a readily retrievable form. Therefore, a Terrain Modeller was developed which assembled and maintained a rectangular grid map of the planet. The third function consisted of directing the vehicle's actions.

Longendorfer, B. A.↗

Control elements for an unmanned Martian roving vehicle

The roving vehicle simulator was operated autonomously under control of the simulated on-board computer. With the microwave radar obstacle sensor mounted and operating, it was able to avoid a student placed in its path and to return to the originally assigned direction when that path was clear. The tactile obstacle sensor was able to detect impassable obstacles while allowing the vehicle to negotiate passable obstacles.

Wehe, R. L.↗

Numerical simulation of the atmosphere during a CAT encounter

In an attempt to determine whether clear air turbulence (CAT) which caused a brief, intense turbulence encounter to a jetliner might have been related to gravity waves generated by a line of thunderstorms, local sounding data taken within two hours of the incident have been used as input to a numerical model designed to simulate stratified flow over obstacles. In the model a rigid obstacle at the lower boundary acted as the source of the gravity waves. The model results show a large amplitude disturbance localized over the obstacle at and above flight level, in regions where CAT would be expected. Stratification studies have been conducted, varying the height and shape of the obstacle and the input wind profile. The success of the experiment leads to the conclusion that atmospheric gravity wave simulation can be useful in understanding and possibly avoiding CAT.

Keller, T. L.↗