Decision Making for Rapid Information Acquisition in the Reconnaissance of Random Fields

Research into several aspects of robot-enabled reconnaissance of random fields is reported. The work has two major components: the underlying theory of information acquisition in the exploration of unknown fields and the results of experiments on how humans use sensor-equipped robots to perform a simulated reconnaissance exercise. The theoretical framework reported herein extends work on robotic exploration that has been reported by ourselves and others. Several new figures of merit for evaluating exploration strategies are proposed and compared. Using concepts from differential topology and information theory, we develop the theoretical foundation of search strategies aimed at rapid discovery of topological features (locations of critical points and critical level sets) of a priori unknown differentiable random fields. The theory enables study of efficient reconnaissance strategies in which the tradeoff between speed and accuracy can be understood. The proposed approach to rapid discovery of topological features has led in a natural way to to the creation of parsimonious reconnaissance routines that do not rely on any prior knowledge of the environment. The design of topology-guided search protocols uses a mathematical framework that quantifies the relationship between what is discovered and what remains to be discovered. The quantification rests on an information theory inspired model whose properties allow us to treat search as a problem in optimal information acquisition. A central theme in this approach is that "conservative" and "aggressive" search strategies can be precisely defined, and search decisions regarding "exploration" vs. "exploitation" choices are informed by the rate at which the information metric is changing.Comment: 34 pages, 20 figure

Computer vision-based structural assessment exploiting large volumes of images

Visual assessment is a process to understand the state of a structure based on evaluations originating from visual information. Recent advances in computer vision to explore new sensors, sensing platforms and high-performance computing have shed light on the potential for vision-based visual assessment in civil engineering structures. The use of low-cost, high-resolution visual sensors in conjunction with mobile and aerial platforms can overcome spatial and temporal limitations typically associated with other forms of sensing in civil structures. Also, GPU-accelerated and parallel computing offer unprecedented speed and performance, accelerating processing the collected visual data. However, despite the enormous endeavor in past research to implement such technologies, there are still many practical challenges to overcome to successfully apply these techniques in real world situations. A major challenge lies in dealing with a large volume of unordered and complex visual data, collected under uncontrolled circumstance (e.g. lighting, cluttered region, and variations in environmental conditions), while just a tiny fraction of them are useful for conducting actual assessment. Such difficulty induces an undesirable high rate of false-positive and false-negative errors, reducing the trustworthiness and efficiency of their implementation. To overcome the inherent challenges in using such images for visual assessment, high-level computer vision algorithms must be integrated with relevant prior knowledge and guidance, thus aiming to have similar performance with those of humans conducting visual assessment. Moreover, the techniques must be developed and validated in the realistic context of a large volume of real-world images, which is likely contain numerous practical challenges. In this dissertation, the novel use of computer vision algorithms is explored to address two promising applications of vision-based visual assessment in civil engineering: visual inspection, and visual data analysis for post-disaster evaluation. For both applications, powerful techniques are developed here to enable reliable and efficient visual assessment for civil structures and demonstrate them using a large volume of real-world images collected from actual structures. State-of-art computer vision techniques, such as structure-from-motion and convolutional neural network techniques, facilitate these tasks. The core techniques derived from this study are scalable and expandable to many other applications in vision-based visual assessment, and will serve to close the existing gaps between past research efforts and real-world implementations

Autonomous 3D Exploration of Large Structures Using an UAV Equipped with a 2D LIDAR

This paper addressed the challenge of exploring large, unknown, and unstructured industrial environments with an unmanned aerial vehicle (UAV). The resulting system combined well-known components and techniques with a new manoeuvre to use a low-cost 2D laser to measure a 3D structure. Our approach combined frontier-based exploration, the Lazy Theta* path planner, and a flyby sampling manoeuvre to create a 3D map of large scenarios. One of the novelties of our system is that all the algorithms relied on the multi-resolution of the octomap for the world representation. We used a Hardware-in-the-Loop (HitL) simulation environment to collect accurate measurements of the capability of the open-source system to run online and on-board the UAV in real-time. Our approach is compared to different reference heuristics under this simulation environment showing better performance in regards to the amount of explored space. With the proposed approach, the UAV is able to explore 93% of the search space under 30 min, generating a path without repetition that adjusts to the occupied space covering indoor locations, irregular structures, and suspended obstaclesUnión Europea Marie Sklodowska-Curie 64215Unión Europea MULTIDRONE (H2020-ICT-731667)Uniión Europea HYFLIERS (H2020-ICT-779411

Measuring the Risk of Shortfalls in Air Force Capabilities

The U.S. Air Force seeks to measure and prioritize risk as part of its Capabilities Review and Risk Assessment (CRRA) process. The goal of the CRRA is to identify capability shortfalls, and the risks associated with those shortfalls, to influence future systems acquisition. Many fields, including engineering, medicine and finance, seek to model and measure risks. This research utilizes various risk measurement approaches to propose appropriate risk measures for a military context. Specifically, risk is modeled as a non-negative random variable of severity. Four measures are examined: simple expectation, a risk-value measure, tail conditional expectation, and distorted expectation. Risk measures are subsequently used to weight the objective function coefficients in a system acquisition knapsack problem

Field Study for Remote Sensing: An instructor's manual

The need for and value of field work (surface truthing) in the verification of image identification from high atitude infrared and multispectral space sensor images are discussed in this handbook which presents guidelines for developing instructional and research procedures in remote sensing of the environment

LAND RIGHTS AND INTRA-HOUSEHOLD EMPLOYMENT AND RESOURCE USE IN THE PERI-URBAN AREA OF BANJUL, THE GAMBIA

As part of cooperative research program examining factor markets in peri-urban areas of The Gambia (Banjul and Serekunda) to see if they are constraining agricultural growth and employment, particularly in the horticultural subsector, the household production survey reported in this study assesses inter- and intrahousehold issues of market access and constraints to land-improving investment and productivity. Implemented in 1993, survey is highly disaggregated by plot, gender, enterprise, and type of employment.Land tenure--Gambia--Banjul Region, Vendors and purchasers--Gambia--Banjul Region, Household production--Gambia, Research methods, Rural conditions--Gambia, Rural off-farm employment--Gambia, Income and wealth--Gambia, Land markets--Gambia, Tenure types, Traditional--Gambia, Labor and Human Capital, Land Economics/Use,

World weather program: Plan for fiscal year 1972

The World Weather Program which is composed of the World Weather Watch, the Global Atmospheric Research Program, and the Systems Design and Technological Development Program is presented. The U.S. effort for improving the national weather services through advances in science, technology and expanded international cooperation during FY 72 are described. The activities of the global Atmospheric Research Program for last year are highlighted and fiscal summary of U.S. programs is included

Post-Westgate SWAT : C4ISTAR Architectural Framework for Autonomous Network Integrated Multifaceted Warfighting Solutions Version 1.0 : A Peer-Reviewed Monograph

Police SWAT teams and Military Special Forces face mounting pressure and challenges from adversaries that can only be resolved by way of ever more sophisticated inputs into tactical operations. Lethal Autonomy provides constrained military/security forces with a viable option, but only if implementation has got proper empirically supported foundations. Autonomous weapon systems can be designed and developed to conduct ground, air and naval operations. This monograph offers some insights into the challenges of developing legal, reliable and ethical forms of autonomous weapons, that address the gap between Police or Law Enforcement and Military operations that is growing exponentially small. National adversaries are today in many instances hybrid threats, that manifest criminal and military traits, these often require deployment of hybrid-capability autonomous weapons imbued with the capability to taken on both Military and/or Security objectives. The Westgate Terrorist Attack of 21st September 2013 in the Westlands suburb of Nairobi, Kenya is a very clear manifestation of the hybrid combat scenario that required military response and police investigations against a fighting cell of the Somalia based globally networked Al Shabaab terrorist group.Comment: 52 pages, 6 Figures, over 40 references, reviewed by a reade

Remote sensing of aquatic plants

Various sensors were tested in terms of their ability to detect and discriminate among noxious aquatic macrophytes. A survey of researchers currently studying the problem and a brief summary of their work is included. Results indicated that the sensor types best suited to assessment of the aquatic environment are color, color infrared, and black-and-white infrared film, which furnish consistently high contrasts between aquatic plants and their surroundings