Modeling and simulation of future capabilities with an automated computer-aided wargame

2019 ◽  
pp. 154851291987398
Author(s):  
John Langreck ◽  
Hermann Wong ◽  
Alejandro Hernandez ◽  
Stephen Upton ◽  
Mary McDonald ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Large Scale ◽  
Underwater Vehicles ◽  
Unmanned Underwater Vehicles ◽  
Aerial Vehicles ◽  
Computer Aided ◽  
High Level ◽  
Global Operations ◽  
The Impact ◽  
Inform Decision Making

This article explores the development and application of an automated computer-aided wargame to establish high-level capability requirements and concepts of operations for future Navy unmanned aerial vehicles and unmanned underwater vehicles. The Joint Theater Level Simulation-Global Operations serves as the modeling environment, in which a computer-aided exercise models the impact of future intelligence, surveillance, and reconnaissance assets. Automating wargame simulations permits the replication of a large-scale exercise without the continued investment of support personnel and operating units. The environment enables experimentation that provides force planners with pertinent metrics to inform decision-making.

A method for autonomous collision-free navigation of a quadrotor UAV in unknown tunnel-like environments

Robotica ◽  
2021 ◽  
pp. 1-27
Author(s):  
Taha Elmokadem ◽  
Andrey V. Savkin
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Autonomous Underwater Vehicles ◽  
Three Dimensional ◽  
Underwater Vehicles ◽  
Practical Implementation ◽  
Challenging Problem ◽  
Quadrotor Uav ◽  
Navigation Algorithm ◽  
Aerial Vehicles ◽  
Quadrotor Uavs

Abstract Unmanned aerial vehicles (UAVs) have become essential tools for exploring, mapping and inspection of unknown three-dimensional (3D) tunnel-like environments which is a very challenging problem. A computationally light navigation algorithm is developed in this paper for quadrotor UAVs to autonomously guide the vehicle through such environments. It uses sensors observations to safely guide the UAV along the tunnel axis while avoiding collisions with its walls. The approach is evaluated using several computer simulations with realistic sensing models and practical implementation with a quadrotor UAV. The proposed method is also applicable to other UAV types and autonomous underwater vehicles.

scholarly journals A CloudSat–CALIPSO View of Cloud and Precipitation Properties across Cold Fronts over the Global Oceans

2015 ◽  
Vol 28 (17) ◽  
pp. 6743-6762 ◽  
Author(s):  
Catherine M. Naud ◽  
Derek J. Posselt ◽  
Susan C. van den Heever
Keyword(s):  
Large Scale ◽  
Cold Front ◽  
Conveyor Belt ◽  
Low Level ◽  
Scale Parameters ◽  
Convective Clouds ◽  
Cold Fronts ◽  
Surface Front ◽  
High Level ◽  
The Impact

Abstract The distribution of cloud and precipitation properties across oceanic extratropical cyclone cold fronts is examined using four years of combined CloudSat radar and CALIPSO lidar retrievals. The global annual mean cloud and precipitation distributions show that low-level clouds are ubiquitous in the postfrontal zone while higher-level cloud frequency and precipitation peak in the warm sector along the surface front. Increases in temperature and moisture within the cold front region are associated with larger high-level but lower mid-/low-level cloud frequencies and precipitation decreases in the cold sector. This behavior seems to be related to a shift from stratiform to convective clouds and precipitation. Stronger ascent in the warm conveyor belt tends to enhance cloudiness and precipitation across the cold front. A strong temperature contrast between the warm and cold sectors also encourages greater post-cold-frontal cloud occurrence. While the seasonal contrasts in environmental temperature, moisture, and ascent strength are enough to explain most of the variations in cloud and precipitation across cold fronts in both hemispheres, they do not fully explain the differences between Northern and Southern Hemisphere cold fronts. These differences are better explained when the impact of the contrast in temperature across the cold front is also considered. In addition, these large-scale parameters do not explain the relatively large frequency in springtime postfrontal precipitation.

scholarly journals Enhanced Particle Swarm Optimization for Path Planning of Unmanned Aerial Vehicles

2020 ◽  
Vol 14 (1) ◽  
pp. 67-78
Author(s):  
Kai Yit Kok ◽  
Parvathy Rajendran
Keyword(s):  
Particle Swarm Optimization ◽  
Path Planning ◽  
Unmanned Aerial Vehicles ◽  
Particle Swarm ◽  
Swarm Optimization ◽  
Aerial Vehicles ◽  
Trial And Error Method ◽  
The Impact ◽  
Enhanced Particle Swarm Optimization ◽  
Error Method

This paper presents an enhanced particle swarm optimization (PSO) for the path planning of unmanned aerial vehicles (UAVs). An evolutionary algorithm such as PSO is costly because every application requires different parameter settings to maximize the performance of the analyzed parameters. People generally use the trial-and-error method or refer to the recommended setting from general problems. The former is time consuming, while the latter is usually not the optimum setting for various specific applications. Hence, this study focuses on analyzing the impact of input parameters on the PSO performance in UAV path planning using various complex terrain maps with adequate repetitions to solve the tuning issue. Results show that inertial weight parameter is insignificant, and a 1.4 acceleration coefficient is optimum for UAV path planning. In addition, the population size between 40 and 60 seems to be the optimum setting based on the case studies.

scholarly journals Computational Modeling of the Human Microbiome

2020 ◽  
Vol 8 (2) ◽  
pp. 197
Author(s):  
Shomeek Chowdhury ◽  
Stephen S. Fong
Keyword(s):  
Computational Modeling ◽  
Human Health ◽  
Large Scale ◽  
Human Microbiome ◽  
Human Microbiome Project ◽  
Microbial Composition ◽  
Site Specific ◽  
Microbiome Research ◽  
High Level ◽  
The Impact

The impact of microorganisms on human health has long been acknowledged and studied, but recent advances in research methodologies have enabled a new systems-level perspective on the collections of microorganisms associated with humans, the human microbiome. Large-scale collaborative efforts such as the NIH Human Microbiome Project have sought to kick-start research on the human microbiome by providing foundational information on microbial composition based upon specific sites across the human body. Here, we focus on the four main anatomical sites of the human microbiome: gut, oral, skin, and vaginal, and provide information on site-specific background, experimental data, and computational modeling. Each of the site-specific microbiomes has unique organisms and phenomena associated with them; there are also high-level commonalities. By providing an overview of different human microbiome sites, we hope to provide a perspective where detailed, site-specific research is needed to understand causal phenomena that impact human health, but there is equally a need for more generalized methodology improvements that would benefit all human microbiome research.

scholarly journals Approaching birds with drones: first experiments and ethical guidelines

2015 ◽  
Vol 11 (2) ◽  
pp. 20140754 ◽  
Author(s):  
Elisabeth Vas ◽  
Amélie Lescroël ◽  
Olivier Duriez ◽  
Guillaume Boguszewski ◽  
David Grémillet
Keyword(s):  
Best Practices ◽  
Unmanned Aerial Vehicles ◽  
Ecological Research ◽  
Ethical Guidelines ◽  
Wetland Area ◽  
Physiological Indicators ◽  
Approach Distance ◽  
Aerial Vehicles ◽  
Approach Speed ◽  
The Impact

Unmanned aerial vehicles, commonly called drones, are being increasingly used in ecological research, in particular to approach sensitive wildlife in inaccessible areas. Impact studies leading to recommendations for best practices are urgently needed. We tested the impact of drone colour, speed and flight angle on the behavioural responses of mallards Anas platyrhynchos in a semi-captive situation, and of wild flamingos ( Phoenicopterus roseus ) and common greenshanks ( Tringa nebularia ) in a wetland area. We performed 204 approach flights with a quadricopter drone, and during 80% of those we could approach unaffected birds to within 4 m. Approach speed, drone colour and repeated flights had no measurable impact on bird behaviour, yet they reacted more to drones approaching vertically. We recommend launching drones farther than 100 m from the birds and adjusting approach distance according to species. Our study is a first step towards a sound use of drones for wildlife research. Further studies should assess the impacts of different drones on other taxa, and monitor physiological indicators of stress in animals exposed to drones according to group sizes and reproductive status.

scholarly journals Methodological Ambiguity and Inconsistency Constrain Unmanned Aerial Vehicles as A Silver Bullet for Monitoring Ecological Restoration

2019 ◽  
Vol 11 (10) ◽  
pp. 1180 ◽  
Author(s):  
Todd M. Buters ◽  
Philip W. Bateman ◽  
Todd Robinson ◽  
David Belton ◽  
Kingsley W. Dixon ◽  
...  
Keyword(s):  
Machine Learning ◽  
Unmanned Aerial Vehicles ◽  
Ecological Restoration ◽  
Large Scale ◽  
Ecological Monitoring ◽  
Policy Framework ◽  
Strong Positive Correlation ◽  
Aerial Vehicles ◽  
The Future ◽  
Thermal Cameras

The last decade has seen an exponential increase in the application of unmanned aerial vehicles (UAVs) to ecological monitoring research, though with little standardisation or comparability in methodological approaches and research aims. We reviewed the international peer-reviewed literature in order to explore the potential limitations on the feasibility of UAV-use in the monitoring of ecological restoration, and examined how they might be mitigated to maximise the quality, reliability and comparability of UAV-generated data. We found little evidence of translational research applying UAV-based approaches to ecological restoration, with less than 7% of 2133 published UAV monitoring studies centred around ecological restoration. Of the 48 studies, > 65% had been published in the three years preceding this study. Where studies utilised UAVs for rehabilitation or restoration applications, there was a strong propensity for single-sensor monitoring using commercially available RPAs fitted with the modest-resolution RGB sensors available. There was a strong positive correlation between the use of complex and expensive sensors (e.g., LiDAR, thermal cameras, hyperspectral sensors) and the complexity of chosen image classification techniques (e.g., machine learning), suggesting that cost remains a primary constraint to the wide application of multiple or complex sensors in UAV-based research. We propose that if UAV-acquired data are to represent the future of ecological monitoring, research requires a) consistency in the proven application of different platforms and sensors to the monitoring of target landforms, organisms and ecosystems, underpinned by clearly articulated monitoring goals and outcomes; b) optimization of data analysis techniques and the manner in which data are reported, undertaken in cross-disciplinary partnership with fields such as bioinformatics and machine learning; and c) the development of sound, reasonable and multi-laterally homogenous regulatory and policy framework supporting the application of UAVs to the large-scale and potentially trans-disciplinary ecological applications of the future.

scholarly journals The Wane of Command: Evidence on Drone Strikes and Control within Terrorist Organizations

2020 ◽  
pp. 1-20
Author(s):  
ANOUK S. RIGTERINK
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Natural Experiment ◽  
Terrorist Attacks ◽  
Terrorist Organizations ◽  
Aerial Vehicles ◽  
Terrorist Groups ◽  
Drone Strikes ◽  
And Control ◽  
The Impact ◽  
Better Than

This paper investigates how counterterrorism targeting terrorist leaders affects terrorist attacks. This effect is theoretically ambiguous and depends on whether terrorist groups are modeled as unitary actors or not. The paper exploits a natural experiment provided by strikes by Unmanned Aerial Vehicles (drones) “hitting” and “missing” terrorist leaders in Pakistan. Results suggest that terrorist groups increase the number of attacks they commit after a drone “hit” on their leader compared with after a “miss.” This increase is statistically significant for 3 out of 6 months after a hit, when it ranges between 47.7% and 70.3%. Additional analysis of heterogenous effects across groups and leaders, and the impact of drone hits on the type of attack, terrorist group infighting, and splintering, suggest that principal-agent problems—(new) terrorist leaders struggling to control and discipline their operatives—account for these results better than alternative theoretical explanations.

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