Autonomous Vehicles in Support of Naval Operations
... As the autonomy technology advances, the number of human operators per underwater robot will be significantly reduced [7] within the very near future. To enable a single human operator controlling one or multiple robots, it is of particular importance to build mutual trust between a human operator and underwater robots. ...
... Data: T n (t), {I n , L n } N n=1 Result: {I n , L n } N n=1 1 for each τ n ∈ Γ do 2 T n,max = max t−Ln≤t≤t T n (t); 3 T n,min = min t−Ln≤t≤t T n (t); 4if T n,max > T n,u − 1 or T n,min > T n,d then5 I n = min{I n + 1, L n } ; 6 else if T n,min < T n,l + 2 or T n,max < T n,d then7 I n = max{I n − 1, 0} ; 8 return {I n , L n } N n=1 ; An example of periodic trust-based control strategy between the human operator and one robot ...
It is envisioned that a human operator is able to monitor and control one or more (semi)autonomous underwater robots simultaneously in future marine operations. To enable such operations, a human operator must trust the capability of a robot to perform tasks autonomously, and the robot must establish its trust to the human operator based on human performance and follow guidance accordingly. Therefore, we seek to i model the mutual trust between humans and robots (especially (semi)autonomous underwater robots in this chapter), and ii) develop a set of trust-based algorithms to control the human-robot team so that the mutual trust level can be maintained at a desired level. We propose a time series based mutual trust model that takes into account robot performance, human performance and overall human-robot system fault rates. The robot performance model captures the performance evolution of a robot under autonomous mode and teleoperated mode, respectively. Furthermore, we specialize the robot performance model of a YSI EcoMapper autonomous underwater robot based on its distance to a desired waypoint. The human performance model is inspired by the Yerkes-Dodson law in psychology, which describes the relationship between human arousal and performance. Based on the mutual trust model, we first study a simple case of one human operator controlling a single robot and propose a trust-triggered control strategy depending on the limit conditions of the desired trust region. The method is then enhanced for the case of one human operator controlling a swarm of robots. In this framework, a periodic trust-based control strategy with a highest-trust-first scheduling algorithm is proposed. Matlab simulation results are provided to validate the proposed model and control strategies that guarantee effective real-time scheduling of teleoperated and autonomous controls in both one human one underwater robot case and one human multiple underwater robots case.
... However, some new researches used additional power supplies such as; photovoltaic and fuel cell as ancillary power supply. Challenges face electrical power systems in UAVs are much more critical than in other applications [5,6]. Topics below studied challenges faces UAV power system. ...
... As illustrated in [5,6] the electrical faults in UAV electrical power system is much more critical than in other application. The electrical fault can damage for filter capacitors, switched and any sensitive components in the network [6,20,21]. ...
Unmanned Aerial Vehicle (UAV) has evolved rapidly over the past decade. There have been an increased number of studies aiming at improving UAV and in its use for different civil applications. This paper highlights the fundamentals of UAV system and examines the challenges related with the major components such as motors, drives, power systems, communication systems and image processing tools and equipment.
... As the labor cost increases and the autonomy technology advances, the number of human operators per agent has been reduced to a large extent. In future operations, it is envisioned that one human operator can work with multiple agents [3], [27]. In this pursuit, building mutual trust between human operators and (semi)autonomous agents is of particular importance since mutual trust is the basis of collaboration, which may improve task efficiency and reduce risks and errors. ...
Mutual trust is a key factor in human–human collaboration. Inspired by this social interaction, we analyse human–agent mutual trust in the collaboration of human and (semi)autonomous multi-agent systems. Human–agent mutual trust should be bidirectional and determines the human’s acceptance and hence use of autonomous agents as well as agents’ willingness to take human’s command. It is especially important when a human collaborates with multiple agents concurrently. In this paper, we derive time-series human–agent mutual trust models based on results from human factors engineering. To avoid both ‘over-trust’ and ‘under-trust’, we set up dynamic timing models for the multi-agent scheduling problem and develop necessary and sufficient conditions to test the schedulability of the human multi-agent collaborative task. Our simulation results show that the proposed algorithm guarantees effective real-time scheduling of the human multi-agent collaboration system while ensuring a proper level of human–agent mutual trust.
... The Office of the Secretary of Defense's Roadmap for Unmanned Systems calls for improvements in multi-vehicle supervisory control capabilities 5 . The Committee on Autonomous Vehicles in Support of Naval Operations also considers that it is important to carryout such research 6 . There is a great deal of literature available on different aspects of multiple UAVs control. ...
Although UAV systems are currently controlled by a group of people, in the future, increased automation could allow a single operator to supervise multiple UAVs. Operators will be involved in the mission planning, imagery analysis, weapon control, and contingency interventions. This study examines the architecture and prototype of multiple UAVs supervisory control system. Firstly, the architecture for testing and evaluating human supervisory system controlling multiple UAVs is devised and each sub-system is described in detail. Then a prototype test bed of multiple UAVs supervisory control for demonstrating architecture and adaptive levels of autonomy is built. Finally, with the test bed, the impact of dynamic role allocation on system performance is studied based on quantitative criteria of wait times and operator utilisation. It is shown by simulation that dynamic role allocation can effectively shorten wait times, and eventually improve the system performance.Defence Science Journal, Vol. 65, No. 2, March 2015, pp.93-98, DOI:http://dx.doi.org/10.14429/dsj.65.5837
... These requirements, as well as the dynamic nature of the flight deck, require that the schedule also be computed in the minimum time possible. The inclusion of unmanned aerial vehicles (UAVs) in the near future [19] provides a foothold for automating a variety of aircraft actions on the flight deck. Northrop Grumman's X-47B Pegasus UAV will demonstrate point-and-click control, in which the vehicle will receive abstract commands such as " taxi to this catapult and takeoff " [20]. ...
... uture naval operations in the littoral environment are expected to make extensive use of coordinated unmanned vehicle teams to support a range of operations, including intelligence, surveillance, and reconnaissance (ISR), as well as anti-terrorism/force protection (AT/FP), suppression of enemy air defenses (SEAD), and anti-mine and antisubmarine warfare (AMW, ASW). 1,2 While great strides are being made in the development of unmanned aerial, undersea and surface vehicles (collectively UVs), the development of advanced operational capabilities that will effectively support the autonomous operation of heterogeneous teams of these vehicles with minimal human intervention is proceeding more slowly. Within the scope of the Intelligent Autonomy program, the Office of Naval Research (ONR) is pursuing technological advancements to support future operations in the littoral environment by developing advanced autonomous mission planning and execution technologies for heterogeneous teams of UVs. ...
Future unmanned systems in the military will be highly heterogeneous in nature, with vehicles from multiple domains—aerial, underwater, and land—working in collaborative teams to complete a variety of missions. The complexity of supervising these teams will be enormous and will rely on human creativity, judgment, and experience. Therefore, the design and development of mission planning and monitoring technologies must be rooted in a deep understanding of the human operator's role as mission manager, and must effectively address the reasoning skills and limitations of both the human and autonomous intelligent system. In this paper we present our work to approach these supervisory issues from a human-centered perspective. We first review the findings of a cognitive task analysis, through which we defined critical informational requirements and developed display interfaces for human operators developing and executing mission plans for a small team of underwater and aerial unmanned vehicles. These findings raise several operations issues for unmanned vehicle management, namely (1) vehicle and task heterogeneity and (2) the coordination of command and control across a vehicle team. We discuss the impact of both of these design requirements on the human-centered development of mission planning tools for unmanned systems. Finally, we introduce an investigative approach to support the rapid evaluation of interfaces that flexibly accommodate alternative command and control philosophies for heterogeneous automated systems using a combination of modeling and human-in-the-loop evaluation processes
... Systems of autonomous agents are capable of executing a wide array of complex coordinated tasks, and as such have been subject of significant research efforts. The role of autonomy is manifesting at all levels of the system architecture, and increasingly, an integrated approach combining information feedback, probabilistic modeling, and optimization methods is necessary to achieve the complex task in an efficient and effective manner [1], [2]. ...
This paper presents an algorithmic framework for conducting search and identification missions using multiple heterogeneous agents. Dynamic objects of type ldquoneutralrdquo or ldquotargetrdquo move through a discretized environment. Probabilistic representation of the current level of situational awareness - knowledge or belief of object locations and identities - is updated with imperfect observations. Optimization of search is formulated as a mixed-integer program to maximize the expected number of targets found and solved efficiently in a receding horizon approach. The search effort is conducted in tandem with object identification and target interception tasks, and a method for assignment of these missions among agents is developed. The proposed framework is demonstrated in simulation studies, and an implementation of its decision support capabilities in a recent field experiment is reported.
... The intruder is human-competitive in the sense that its attacking efficiency approaches the attacking efficiency of deceptive strategies exhibited by human operators. Our aim is to reach the level 3 of autonomy as defined in Board (2005). In this level, the unmanned vehicle automatically executes missionrelated commands when response times are too short for operator intervention. ...
We address the problem of automated action selection policy synthesis for unmanned vehicles operating in adverse environments. We introduce a new evolutionary computation-based approach using which an initial version of the policy is automatically generated and then gradually refined by detecting and fixing its shortcomings. The synthesis technique consists of the automated extraction of the vehicle’s exception states and Genetic Programming (GP) for automated composition and optimization of corrective sequences of commands in the form of macro-actions to be applied locally.
The focus is specifically on automated synthesis of a policy for Unmanned Surface Vehicle (USV) to efficiently block the advancement of an intruder boat toward a valuable target. This task requires the USV to utilize reactive planning complemented by short-term forward planning to generate specific maneuvers for blocking. The intruder is human-competitive and exhibits a deceptive behavior so that the USV cannot exploit regularity in its attacking behavior.
We compared the performance of a hand-coded blocking policy to the performance of a policy that was automatically synthesized. Our results show that the performance of the automatically generated policy exceeds the performance of the hand-coded policy and thus demonstrates the feasibility of the proposed approach.
Transportation is an integral and fundamental part of human beings’ lives. On Earth, we need transportation in the form of cars, buses, trains, etc. We need aircraft in the air and ships at sea for long-distance transportation. We need space shuttles in space to travel beyond the air. The main desire of human beings is to complete tasks with less energy, effort, time, and more security. The whole paradigm of humanity’s lifestyle can be shifted by autonomous transport (AT), which is already deployed in different technologically advanced countries. The Autonomous Transport System (ATS) is more secure and reliable than the current system of conventional transportation. With the aid of machine learning (ML), artificial intelligence (AI), and blockchain technologies, ultra-fast processing computers can make autonomous vehicles smarter, safer, and more secure than ever before. Connecting vehicles can communicate with the infrastructure to alert the driver about events such as when a train is coming, when a driver cannot see or hear the approaching train, etc. ATS can have a tremendous effect on all we do. However, there are certain challenges involved with every technology, and once we overcome these problems, these ATS can make life simpler, smarter, and safer. Furthermore, we discuss the challenges and future directions for the ATS.
Uncrewed autonomous vehicles (UAVs) have made significant contributions to reconnaissance and surveillance missions in past US military campaigns. As the prevalence of UAVs increases, there has also been improvements in counter-UAV technology that makes it difficult for them to successfully obtain valuable intelligence within an area of interest. Hence, it has become important that modern UAVs can accomplish their missions while maximizing their chances of survival. In this work, we specifically study the problem of identifying a short path from a designated start to a goal, while collecting all rewards and avoiding adversaries that move randomly on the grid. We also provide a possible application of the framework in a military setting, that of autonomous casualty evacuation. We present a comparison of three methods to solve this problem: namely we implement a Deep Q-Learning model, an ε\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\varepsilon$$\end{document}-greedy tabular Q-Learning model, and an online optimization framework. Our computational experiments, designed using simple grid-world environments with random adversaries showcase how these approaches work and compare them in terms of performance, accuracy, and computational time.
Expected to operate in the imminent future, air taxi service (ATS) is an aerial on-demand transport for a single passenger or a small group of riders, which seeks to transform the method of everyday commute. This uncharted territory in the emerging transportation world is anticipated to enable consumers bypass traffic congestion in urban road networks. By adopting an electric vertical takeoff and landing concept (eVTOL), air taxis could be operational from skyports retrofitted on building rooftops, thus gaining advantage from an implementation standpoint. Motivated by the potential impact of ATS, this study provides a review of air taxi systems and associated operations. We first discuss the current developments in the ATS (demand prediction, air taxi network design, and vehicle configuration). Next, we anticipate potential future challenges of ATS from an operations management perspective, and review the existing literature that could be leveraged to tackle these problems (ride-matching, pricing strategies, vehicle maintenance scheduling, and pilot training and recruitment). Finally, we detail future research opportunities in the air taxi domain.
An unmanned underwater vehicle (UUV) or autonomous underwater vehicle (AUV) is a marine robot [1] used for a wide range of oceanographic and military tasks including underwater surveys, inspection of submerged structures, tracking oceanographic features, undersea mapping, laying undersea cable, searching for downed aircraft, and finding naval sea mines, to name but a few. An unmanned surface vehicle (USV) is also categorized as a marine robot; however, most of this book is concerned with UUVs. In terms of physical shape, UUVs can be the traditional torpedo-shaped bodies as shown in Fig. 1 or an underwater glider such as that seen in Fig. 2. At the lowest level of control, UUVs operate with closed-loop control for basic actions such as maintaining depth, pitch, roll, and heading. As an extension to this capability, UUVs can also line-follow between a series of waypoints while logging data from mission sensors, as well as sensors that monitor the UUV status and functionality. Such basic actions can be grouped into behaviours.
The Surveying Coastal Ocean Autonomous Profiler (SCOAP) is a large catamaran marine autonomous surface craft (MASC) for unattended weeks-long, spatially explicit, multidisciplinary oceanographic water column profile sampling in coastal/estuarine waterbodies. Material transport rates/pathways, crucial to understanding these ecosystems, are typically poorly known. SCOAP addresses demanding spatiotemporal sampling needs and operational challenges (strong currents, open coastal sea states, complex bathymetry, heavy vessel traffic). Its large size (11-m length, 5-m beam) provides seaworthiness/stability. The average speed of 2.5 m s 21 meets the representative goal to traverse an 18-km transect, sampling 10 min at each of 10 stations 2 km apart, nominally 4 times daily. Efficient hulls and a diesel–electric energy system can provide the needed endurance. The U.S. Coast Guard guidelines are followed: lighting, code flags, the Automatic Identification System (AIS), and collision avoidance regulations (COLREGs)-based collision avoidance (CA) by onboard autonomy software. Large energy reserves obviate low-power optimization of sensors, enabling truly multidisciplinary sampling, and provide on-demand propulsion for effective CA. Vessel stability facilitates high-quality current profile observations and will aid engineering/operation of the planned winched profiling system, performance of an anticipated radar system to detect/track non-AIS vessels, and potential research-quality meteorological sensor operation. A Narragansett Bay test deployment, attended by an escort vessel, met design goals; an unattended open coastal deployment is planned for Rhode Island Sound. Scientific and operational strengths of large catamaran MASCs suggest they could be an important cost-effective complement to other sampling platforms (e.g., improved spatiotemporal coverage and resolution, extending farther inshore, with a broader range of sensors, compared to underwater gliders) in coastal/ estuarine waters.
Being able to define and measure the performance of guidance systems is fundamental to their proper development. This task is particularly challenging for unmanned aerial vehicles operating in complex spatial environment like cities or mountains, both of which are operational theaters of predilection. Previous research mainly focuses on relative per-formance metrics. This paper, introduces a framework to derive absolute metrics. The approach is based on the idea that many guidance problems have a meaningful formulation as an optimal control problem. Hence the idea is that absolute performance metrics can be based on an approximation of the optimal control problem. In the following we ap-proximate the vehicle dynamics using motion primitives. The choice of motion primitives is based on an analysis of the vehicle flight performance based on experimental data. As performance metric, we use the approximate cost-to-go maps and associated optimal states computed via dynamic programming for a cell-based world representation. The cost-to-go map, which can be computed for any environment described by Digital Terrain Elevation Data (DTED), provides a comprehensive insight into the interrelation of space, optimal be-havior, as driven by a user specified performance index. The only limitation in the choice of performance index is that it should be a function of attributes of the finite state motion primitives. The paper illustrates the method applied to an unmanned R-MAX helicopter (10ft rotor diameter) operating in the down town of San Francisco. Three performance indexes are analyzed: time, energy and length.
This thesis discusses piracy on the open seas. It describes acts of piracy, puts the practice into historical perspective, and shows how a recent surge in maritime piracy incidents differs from other maritime piracy afflicting the world's oceans at the turn of the twentyfirst century. This is half of the reason for writing. The second purpose for is to examine the US military response to the dramatic increase in piracy near Somalia that occurred in 2008. The thesis examines the US response through the theoretical lenses of strategic culture and structural realism. These theories seldom appear alongside each other in security studies literature; their juxtaposition explains the US behavior toward the contemporary African piracy epidemic and provides a framework for examining other national security issues. This thesis concludes that although certain national security elites push US strategic culture toward interventionist or isolationist extremes, some world events elicit foregone responses best described by the ideas of structural realism. Tacit realization by national security actors that these events exist in spite of what elite groups profess or desire in turn defines strategic culture in a fundamentally different way. Given its place in the existing world order, the United States had little choice but to respond to piracy, even though its strategic preference was to ignore the problem. The valuable lesson from piracy represents in microcosm many problems of national strategy. If US cultural preference is again at odds with a strategic imperative to use force, and elites indulge the former, the nation may forfeit its structural role as the world's existing hegemon. This is historically significant, as ceding the role of hegemon at this time would be a voluntary act, not forced by a stronger nation or an altered balance of power. The United States would become the first suAlthough US foreign
The rapid evolution of cyber technologies demands a new concept of Network-Centric Warfare - a new construct built on the foundation of the new interactive web. The rapid advancement of information technologies and the development of cloud computing by large commercial information technology trendsetter organizations like Google, should lead the Department of Defense to ask: does cloud computing represent the future of network-centric operations and warfare for the United States military? For the Department of Defense to embrace cloud computing requires it to adopt the internet, rather than a fixed IT infrastructure, as its network backplane. The Department will be required to rapidly embrace and employ new Network-Centric concepts (referred to in this paper as Network-Centric Warfare 2.0) and address issues such as cost; military operations in a collaborative environment; empowering individuals; granting greater access to Department and Service specific information; developing processes and procedures for new parallel and serial operations; and rapidly developing and employing new technologies to provide enhanced data fusion capabilities.
This paper outlines the development of the Wind and Solar Powered Autonomous Surface Vehicle (WASP), an unmanned autonomous long-range surface vehicle. We aim to develop mission specific systems to forecast environmental events and to trace the distribution of meteorological and ocean conditions over a long-term period (about 6 months at a time). The WASP consists of a 2.4 Meter Class Sailboat hull, a composite wing, a 2000 Watt-hour battery reservoir, a system of control actuators, a control system running from a LPC 2138 Development Board, a suite of oceanographic sensors, and potential power regeneration from both solar and wind energy. This paper briefly discusses the motivation for such system development, adresses key aspects of the design, comments on modeling, and concludes with recommendations of future work.
In response to an expression of interest by the U.S. Navy, ASTM International and the Association for Unmanned Vehicle Systems International (AUVSI) embarked upon the process of developing technical standards for unmanned undersea vehicles (UUVs.) In 2005 a formal committee was formed under ASTM's established and recognized standards development procedures. ASTM Committee F41 on Unmanned Vehicle Systems is working on the development of technical standards for autonomy, mission payloads, sensors, communications interfaces and data. These standards are initially intended to support the U.S. Navy Mission Reconfigurable UUV System (MRUUVS) program. They will be referenced in the MRUUVS request for proposals and ideally they will improve the eventual MRUUV system. This paper discusses the history of the standards development, the content of the standards which will go to ballot in June 2005 and the potential applicability of these standards to UUVs beyond the U.S. Navy's large diameter UUV programs
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