DOCSLIB.ORG

An Autonomous Unmanned Aerial Vehicle-Based Imagery System Development and Remote Sensing Images Classification for Agricultural Applications

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
An Autonomous Unmanned Aerial Vehicle-Based Imagery System Development and Remote Sensing Images Classification for Agricultural Applications Utah State University DigitalCommons@USU All Graduate Theses and Dissertations Graduate Studies 12-2009 An Autonomous Unmanned Aerial Vehicle-Based Imagery System Development and Remote Sensing Images Classification for Agricultural Applications Yiding Han Utah State University Follow this and additional works at: https://digitalcommons.usu.edu/etd Part of the Aerospace Engineering Commons Recommended Citation Han, Yiding, "An Autonomous Unmanned Aerial Vehicle-Based Imagery System Development and Remote Sensing Images Classification for Agricultural Applications" (2009). All Graduate Theses and Dissertations. 513. https://digitalcommons.usu.edu/etd/513 This Thesis is brought to you for free and open access by the Graduate Studies at DigitalCommons@USU. It has been accepted for inclusion in All Graduate Theses and Dissertations by an authorized administrator of DigitalCommons@USU. For more information, please contact [email protected]. AN AUTONOMOUS UNMANNED AERIAL VEHICLE-BASED IMAGERY SYSTEM DEVELOPMENT AND REMOTE SENSING IMAGES CLASSIFICATION FOR AGRICULTURAL APPLICATIONS by Yiding Han A thesis submitted in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE in Electrical Engineering Approved: Dr. HuiFang Dou Dr. YangQuan Chen Major Professor Committee Member Dr. Donald Cripps Dr. Byron R. Burnham Committee Member Dean of Graduate Studies UTAH STATE UNIVERSITY Logan, Utah 2009 ii Copyright c Yiding Han 2009 All Rights Reserved iii Abstract An Autonomous Unmanned Aerial Vehicle-Based Imagery System Development and Remote Sensing Images Classification for Agricultural Applications by Yiding Han, Master of Science Utah State University, 2009 Major Professor: Dr. HuiFang Dou Department: Electrical and Computer Engineering This work concentrates on the topic of remote sensing using a multispectral imag- ing system for water management and agriculture applications. The platform, which is a light-weight inexpensive runway-free unmanned aerial vehicle (UAV), namely, AggieAir, is presented initially. A major portion of this work focuses on the development of a light- weight multispectral imager payload for the AggieAir platform, called GhostFoto. The imager is band-reconfigurable, covering both visual red, green, and blue (RGB) and near infrared (NIR) spectrum, and interfaced with UAV on-board computer. The development of the image processing techniques, which are based on the collected multispectral aerial images, is also presented in this work. One application is to perform fully autonomous river tracking for applications such as river water management. Simulation based on aerial mul- tispectral images is done to demonstrate the feasibility of the developed algorithm. Other effort is made to create a systematic method to generate normalized difference vegetation index (NDVI) using the airborne imagery. The GhostFoto multispectral imaging system based on AggieAir architecture is proven to be an innovative and useful tool. (72 pages) iv To my family and friends. v Acknowledgments I would like to thank my advisor, Dr. Dou, for her generous guidance, advice, financial support, and tremendous help when I am stuck with problems. Without her motivation and insights this work would have never been complete. Also, I would like to thank Dr. Chen for giving me this opportunity to join CSOIS and the UAV team, constantly motivating me, generously supporting me financially in the beginning of my master’s program, and the extraordinary insights that he has brought to my work. Also, I would like to thank my committee member, Dr. Cripps, for his comments on my work. I would like to thank all the CSOIS UAV members, without whom my work would have been impossible. I would like to thank Haiyang Chao for being a great role model for me, guiding and helping me in my work, bringing me up to speed initially in the UAV team, and all the late-night pre-flight tests he participated in. I would like to thank Calvin Coopmans for helping me to understand Linux and programming Gumstix, creating those brilliant ideas about AggieAir architecture with me, and all the late-night work he did with me on different projects. I would like to thank Austin Jensen for inviting me into the UAV team in the first place, and all the great work he did for us in managing the team, and the countless flight tests in which he participated. I would like to thank Di Long for building the airframes and hundreds of backup parts for us, and for participating in the flight tests for UAV competition. I would like to thank Hu Sheng for building and donating his Tiger plane for us to participate in the UAV competition. I would also like to thank Chris Hall and Daniel Morgan for their support and advice. Also, for the other members of the CSOIS, the help that they gave me on other projects is truly appreciated. I would like to thank Shayok Mukhopadhyay for the countless late-night work he did with me for the Smartwheel projects and Sumo robots. He has been such a great friend and helped me enormously with my English. I would also like to thank Shelley Rounds for helping me in the Mechatronics lab projects and teaching me the American culture, Varsha Bhambhani for helping me on the Smartwheel project, and Dr. Yan Li for helping me to understand Fractional Order vi Calculus. I would like to thank all the Chinese scholars that visited CSOIS during my master’s program, for supporting me the whole time and sharing the great Chinese meals with me. I would also like to thank my friends and roommates who supported me and made my time at Utah State University enjoyable. Above all, I would like to thank my family in China, especially my mother, for their constant selfless support and unwavering belief in me. Last, but not least, I would like to thank the Utah Water Research Lab for providing funding for this project. Yiding Han vii Contents Page Abstract ....................................................... iii Acknowledgments ............................................... v List of Tables ................................................... ix List of Figures .................................................. x Acronyms ...................................................... xii 1 Introduction ................................................. 1 1.1 Overview ..................................... 1 1.1.1 Unmanned Aerial Vehicle . 1 1.1.2 Remote Sensing and Agriculture . 2 1.2 Motivation . 2 1.3 GhostFoto Multispectral Remote Sensing Platform . 3 1.3.1 Development Background . 3 1.3.2 Hardware Development for GhostFoto . 3 1.3.3 Software Development for GhostFoto . 4 1.3.4 Image Processing . 5 1.4 Contribution and Organization . 5 2 AggieAir Miniature UAV Architecture ........................... 7 2.1 AggieAir System Overview . 9 2.1.1 Airframe . 9 2.1.2 On-Board Electronics . 10 2.1.3 Ground Controls . 12 2.2 Paparazzi . 14 2.2.1 Paparazzi TWOG Board . 14 2.2.2 Ground Station . 14 2.3 Gumstix On-Board Computer . 16 2.3.1 Functionality . 16 2.3.2 Data Flow . 17 2.4 gRAID Image Processing . 19 3 GhostFoto: A Multispectral Remote Sensing Platform .............. 21 3.1 Background and Expectations . 21 3.2 GhostFoto Hardware . 22 3.2.1 Cameras . 22 3.2.2 Near Infrared Camera . 25 3.3 GhostEye ..................................... 26 viii 3.3.1 gPhoto . 27 3.3.2 Periodic Image Capturing . 27 3.3.3 Calculation of Capture Interval . 30 3.3.4 State Machine . 32 3.3.5 Multithreading Architecture . 33 3.3.6 Image Geo-Referencing . 36 3.3.7 Logging and Debugging . 37 3.3.8 Implementation in Gumstix . 37 3.3.9 Configure GhostEye . 37 4 Image Processing ............................................. 39 4.1 RiverTracking .................................. 39 4.1.1 Motivation . 39 4.1.2 Water Area Recognition . 40 4.1.3 River Tracking Mission . 40 4.1.4 River Identification . 42 4.1.5 Way Points Generation . 45 4.1.6 Results .................................. 47 4.2 Vegetation Recognition . 48 4.2.1 Normalized Difference Vegetation Index . 48 4.2.2 White Panel Calibration . 50 5 Conclusion ................................................... 53 5.1 Contribution ................................... 53 5.2 FutureWork ................................... 54 5.2.1 Thermal Infrared Camera . 54 5.2.2 Collaborative Remote Sensing . 55 5.2.3 Implementation of OpenJAUS . 56 5.2.4 General-Purpose GPU-Based Image Processing . 56 References ...................................................... 58 ix List of Tables Table Page 3.1 Specifications of PowerShot SX100 IS and SX110 IS. 24 3.2 Starting transmission wavelength of different NIR filters. 26 4.1 Multispectral imager settings for river tracking mission. 42 x List of Figures Figure Page 2.1 AggieAir system level overview. 8 2.2 Unicorn airframe. 9 2.3 AggieAir 72 inches UAV layout. 10 2.4 Electronic devices inside the main bay. 11 2.5 Underneath the aircraft. 12 2.6 Paparazzi TWOG board. 15 2.7 Paparazzi Center. 15 2.8 Paparazzi Ground Control Station (GCS). 16 2.9 Gumstix Verdex computer-on-module with expansion board. 17 2.10 Data flow of AggieAir airborne system. 18 2.11 Aerial imagery mosaic created by gRAID under WorldWind. 20 3.1 GhostFinger-DC imager using Pentax Optio E10 camera. 22 3.2 Canon PowerShot SX100 IS with and without the cover. 24 3.3 Canon PowerShot SX100 IS and Canon PowerShot SX110 IS. 25 3.4 CCD sensor inside Canon PowerShot SX100 IS, covered by visible light filter. 26 3.5 Software architecture on which GhostEye is based. 28 3.6 Imager footprint. 31 3.7 Flowchart of GhostEye control structure. 32 3.8 Statuses defined in GhostEye state machine. 34 3.9 Multithread architecture of GhostEye. 35 3.10 Inter-thread communication between GhostEye threads. 35 xi 3.11 Inter-thread communication to store geo-referencing data. 36 4.1 NIR and RGB images of a reservoir . 41 4.2 Flight plan of river tracking mission. 42 4.3 NIR and RGB images of river segment. 44 4.4 Histogram of the NIR image. 45 4.5 Binary images of the river. 46 4.6 Dynamic way points generated from the aerial NIR images.
Load more

Recommended publications
  • Autonomous Vehicles in Support of Naval Operations Committee on Autonomous Vehicles in Support of Naval Operations, National Research Council
    Autonomous Vehicles in Support of Naval Operations Committee on Autonomous Vehicles in Support of Naval Operations, National Research Council ISBN: 0-309-55115-3, 256 pages, 6 x 9, (2005) This free PDF was downloaded from: http://www.nap.edu/catalog/11379.html Visit the National Academies Press online, the authoritative source for all books from the National Academy of Sciences, the National Academy of Engineering, the Institute of Medicine, and the National Research Council: • Download hundreds of free books in PDF • Read thousands of books online, free • Sign up to be notified when new books are published • Purchase printed books • Purchase PDFs • Explore with our innovative research tools Thank you for downloading this free PDF. If you have comments, questions or just want more information about the books published by the National Academies Press, you may contact our customer service department toll-free at 888-624-8373, visit us online, or send an email to [email protected]. This free book plus thousands more books are available at http://www.nap.edu. Copyright © National Academy of Sciences. Permission is granted for this material to be shared for noncommercial, educational purposes, provided that this notice appears on the reproduced materials, the Web address of the online, full authoritative version is retained, and copies are not altered. To disseminate otherwise or to republish requires written permission from the National Academies Press. Autonomous Vehicles in Support of Naval Operations http://www.nap.edu/catalog/11379.html AUTONOMOUS VEHICLES IN SUPPORT OF NAVAL OPERATIONS Committee on Autonomous Vehicles in Support of Naval Operations Naval Studies Board Division on Engineering and Physical Sciences THE NATIONAL ACADEMIES PRESS Washington, D.C.
    [Show full text]
  • Mini Unmanned Aerial Systems (UAV) - a Review of the Parameters for Classification of a Mini AU V
    International Journal of Aviation, Aeronautics, and Aerospace Volume 7 Issue 3 Article 5 2020 Mini Unmanned Aerial Systems (UAV) - A Review of the Parameters for Classification of a Mini AU V. Ramesh PS Lovely Professional University, [email protected] Muruga Lal Jeyan Lovely professional university, [email protected] Follow this and additional works at: https://commons.erau.edu/ijaaa Part of the Aeronautical Vehicles Commons Scholarly Commons Citation PS, R., & Jeyan, M. L. (2020). Mini Unmanned Aerial Systems (UAV) - A Review of the Parameters for Classification of a Mini AU V.. International Journal of Aviation, Aeronautics, and Aerospace, 7(3). https://doi.org/10.15394/ijaaa.2020.1503 This Literature Review is brought to you for free and open access by the Journals at Scholarly Commons. It has been accepted for inclusion in International Journal of Aviation, Aeronautics, and Aerospace by an authorized administrator of Scholarly Commons. For more information, please contact [email protected]. PS and Jeyan: Parameters for Classification of a Mini UAV. The advent of Unmanned Aerial Vehicle (UAV) has redefined the battle space due to the ability to perform tasks which are categorised as dull, dirty, and dangerous. UAVs re-designated as Unmanned Aerial Systems (UAS) are now being developed to provide cost effective efficient solutions for specific applications, both in the spectrum of military and civilian usage. US Office of the Secretary of Defense (2013) describes UAS as a “system whose components include the necessary equipment, network, and personnel to control an unmanned aircraft.” In an earlier paper, US Office of the Secretary of Defense (2005) specifies UAV as the airborne element of the UAS and defines UAV as “A powered, aerial vehicle that does not carry a human operator, uses aerodynamic forces to provide vehicle lift, can fly autonomously or be piloted remotely, can be expendable or recoverable, and can carry a lethal or non-lethal payload.” John (2010) provided an excellent historical perspective about the evolution of the UAVs.
    [Show full text]
  • Introduction to Unmanned Aerial Vehicle (UAV) Flight
    Introduction to Unmanned Aerial Vehicle (UAV) Flight PEIMS Code: N1304670 Abbreviation: PRINUAV Grade Level(s): 10-12 Award of Credit: 1.0 Approved Innovative Course • Districts must have local board approval to implement innovative courses. • In accordance with Texas Administrative Code (TAC) §74.27, school districts must provide instruction in all essential knowledge and skills identified in this innovative course. • Innovative courses may only satisfy elective credit toward graduation requirements. • Please refer to TAC §74.13 for guidance on endorsements. Course Description: The Introduction to Unmanned Aerial Vehicle (UAV) Flight course is designed to prepare students for entry-level employment or continuing education in piloting UAV operations. Principles of UAV is designed to instruct students in UAV flight navigation, industry laws and regulations, and safety regulations. Students are also exposed to mission planning procedures, environmental factors, and human factors involved in the UAV industry. Essential Knowledge and Skills: (a) General Requirements. This course is recommended for students in Grades 10-12. Recommended prerequisite: Principles of Transportation Systems. Students shall be awarded one credit for successful completion of this course. (b) Introduction (1) The Transportation, Distribution, and Logistics Career Cluster focuses on planning, management, and movement of people, materials, and goods by road, pipeline, air, rail, and water and related professional support services such as transportation infrastructure planning and management, logistics services, mobile equipment, and facility maintenance. (2) The Introduction to Unmanned Aerial Vehicle (UAV) Flight course is designed to prepare students for entry-level employment or continuing education in piloting UAV operations. Principles of UAV is designed to instruct students in UAV flight navigation, industry laws and regulations, and safety regulations.
    [Show full text]
  • Monash Robotics and Mechatronics Engineering
    MONASH ROBOTICS AND MECHATRONICS ENGINEERING monash.edu/engineering/ robotics-mechatronics WHAT DO ROBOTICS WHAT IS AND MECHATRONICS ROBOTICS AND ENGINEERS DO? Key to robotics and mechatronics engineering is the ability to analyse and design complex MECHATRONICS machines and systems, which often involve automation. Robotics and mechatronics engineers work with instrumentation, sensors and computer systems. They use these to control movement, optimise processes, ENGINEERING? monitor systems and detect faults. Robotics and mechatronics engineers can be found working in transport, manufacturing, healthcare and construction, particularly in Robotics and mechatronics are places where automation can improve efficiency and productivity, and where multidisciplinary fields of engineering reliability and safety are essential to that combine mechanical engineering, engineering operations. computing, electronics and control theory. They design and develop robots to operate in collaboration with humans, and control At the forefront of rapidly transforming technologies, robotics and systems for vehicles, aircraft, machinery, mechatronics engineers work to design robots and improve the production lines and can now be found automation, performance, features and functionality of products working in biotechnology and biomedicine. and systems with a mix of mechanical and electronic components. Being multidisciplinary in nature, robotics and As a robotics or mechatronics engineer you could design aircraft mechatronics engineers are highly skilled at avionics for autonomous drones, build robots for industry or medicine, managing projects and teams which bridge develop systems based on smartphones, or help robots understand the traditional areas of mechanical and human behaviour. Robotics and mechatronics engineering is also electrical engineering. used in the development, design and operation of processes and production lines needed to make most consumer products.
    [Show full text]
  • Optimal Control of a Helicopter Unmanned Aerial Vehicle (UAV)
    Scholars' Mine Masters Theses Student Theses and Dissertations 2011 Optimal control of a helicopter unmanned aerial vehicle (UAV) David John Nodland Follow this and additional works at: https://scholarsmine.mst.edu/masters_theses Part of the Electrical and Computer Engineering Commons Department: Recommended Citation Nodland, David John, "Optimal control of a helicopter unmanned aerial vehicle (UAV)" (2011). Masters Theses. 5417. https://scholarsmine.mst.edu/masters_theses/5417 This thesis is brought to you by Scholars' Mine, a service of the Missouri S&T Library and Learning Resources. This work is protected by U. S. Copyright Law. Unauthorized use including reproduction for redistribution requires the permission of the copyright holder. For more information, please contact [email protected]. i ii OPTIMAL CONTROL OF A HELICOPTER UNMANNED AERIAL VEHICLE (UAV) by DAVID JOHN NODLAND A THESIS Presented to the Faculty of the Graduate School of the MISSOURI UNIVERSITY OF SCIENCE AND TECHNOLOGY In Partial Fulfillment of the Requirements for the Degree MASTER OF SCIENCE IN ELECTRICAL ENGINEERING 2011 Approved by Jagannathan Sarangapani, Advisor Kelvin T. Erickson Maciej Zawodniok iii iii PUBLICATION THESIS OPTION This thesis consists of the following two papers: paper 1, pages 10-57, D. Nodland, H. Zargarzadeh, and S. Jagannathan, “Neural Network-based Optimal Output Feedback Control for Trajectory Tracking of a Helicopter UAV,” to be submitted to IEEE Transactions on Neural Networks, and paper 2, pages 58-91, D. Nodland, A. Ghosh, H. Zargarzadeh, and S. Jagannathan, “Neuro-Optimal Control of an Unmanned Helicopter,” in Journal of Defense Modeling and Simulation Special Issue: Intelligent Behaviors in Military Unmanned Systems, 2012, to appear.
    [Show full text]
  • Unmanned Aircraft System (UAS): Regulatory Framework and Challenges
    Unmanned Aircraft System (UAS): regulatory framework and challenges NAM/CAR/SAM Civil - Military Cooperation Havana, Cuba, 13 – 17 April 2015 Overview • Background • Objective • UAV? • Assumptions • Challenges • Regulatory Framework • UAS in ATM System • Emerging Situational Technologies • Recommendations Background Can an UAS operate in controlled airspace? Which technologies can be used to reduce the impact? UAS in civil applications Improve the regulations for UAS operations ICAO Global ATM operational concept (Doc 9854) UAV: “[a]n unmanned aerial vehicle is a pilotless aircraft, in the sense of Article 8 of the Convention on International Civil Aviation, which is flown without a pilot-in-command on-board and is either remotely and fully controlled from another place (ground, another aircraft, space) or programmed and fully autonomous.” Objective • This presentation provides an overview of the regulatory frameworks for the UAS activities and how to ensure safe operations in the ATS system. • It also addresses regional coordination between States and other stakeholders for UAS operations during natural disaster events. • It explains future challenges of the UAS into the ATM system. 6 Assumptions UAS is another user of the airspace The ATM should be able to allow the UAS operations The activities should include both civil and military air operations The first step is regulatory framework for the UAS in order to ensure safety integrated operations into the ATM system States to disseminate ATS procedures for UAS air operations UAVs applications Demand of RPAS for Military & civil operations International Military operations SAR, Coastguard / coastline and sea-lane monitoring Fire Services and Forestry Fire detection, incident control Owners / operators of model aircraft doing to commercial activity Many non-aviation businesses and entities importing RPAS Aerial photography, Film, video, still, etc.
    [Show full text]
  • Unmanned Aerial Vehicle Operating Mode Classification Using Deep
    aerospace Article Unmanned Aerial Vehicle Operating Mode Classification Using Deep Residual Learning Feature Extraction Carolyn J. Swinney 1,2,* and John C. Woods 1 1 Computer Science and Electronic Engineering Department, University of Essex, Colchester CO4 3SQ, UK; [email protected] 2 Air and Space Warfare Centre, Royal Air Force Waddington, Lincoln LN5 9NB, UK * Correspondence: [email protected] Abstract: Unmanned Aerial Vehicles (UAVs) undoubtedly pose many security challenges. We need only look to the December 2018 Gatwick Airport incident for an example of the disruption UAVs can cause. In total, 1000 flights were grounded for 36 h over the Christmas period which was estimated to cost over 50 million pounds. In this paper, we introduce a novel approach which considers UAV detection as an imagery classification problem. We consider signal representations Power Spectral Density (PSD); Spectrogram, Histogram and raw IQ constellation as graphical images presented to a deep Convolution Neural Network (CNN) ResNet50 for feature extraction. Pre-trained on ImageNet, transfer learning is utilised to mitigate the requirement for a large signal dataset. We evaluate performance through machine learning classifier Logistic Regression. Three popular UAVs are classified in different modes; switched on; hovering; flying; flying with video; and no UAV present, creating a total of 10 classes. Our results, validated with 5-fold cross validation and an independent dataset, show PSD representation to produce over 91% accuracy for 10 classifications. Our paper treats UAV detection as an imagery classification problem by presenting signal representations as images to a ResNet50, utilising the benefits of transfer learning and outperforming previous work in the field.
    [Show full text]
  • Downloadfile/566729524649660/Duartefigueiredo Thesis.Pdf (Accessed on 20 May 2021)
    drones Article Development of a Solar-Powered Unmanned Aerial Vehicle for Extended Flight Endurance Yauhei Chu †, Chunleung Ho †, Yoonjo Lee † and Boyang Li * Department of Aeronautical and Aviation Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, China; [email protected] (Y.C.); [email protected] (C.H.); [email protected] (Y.L.) * Correspondence: [email protected]; Tel.: +852-340-082-31 † Authors have contributed equally. Abstract: Having an exciting array of applications, the scope of unmanned aerial vehicle (UAV) application could be far wider one if its flight endurance can be prolonged. Solar-powered UAV, promising notable prolongation in flight endurance, is drawing increasing attention in the industries’ recent research and development. This work arose from a Bachelor’s degree capstone project at Hong Kong Polytechnic University. The project aims to modify a 2-metre wingspan remote-controlled (RC) UAV available in the consumer market to be powered by a combination of solar and battery-stored power. The major objective is to greatly increase the flight endurance of the UAV by the power generated from the solar panels. The power system is first designed by selecting the suitable system architecture and then by selecting suitable components related to solar power. The flight control system is configured to conduct flight tests and validate the power system performance. Under fair experimental conditions with desirable weather conditions, the solar power system on the aircraft results in 22.5% savings in the use of battery-stored capacity. The decrease rate of battery voltage Citation: Chu, Y.; Ho, C.; Lee, Y.; Li, during the stable level flight of the solar-powered UAV built is also much slower than the same B.
    [Show full text]
  • Design and Autonomous Stabilization of a Ballistically-Launched Multirotor
    Design and Autonomous Stabilization of a Ballistically-Launched Multirotor Amanda Bouman1, Paul Nadan2, Matthew Anderson3, Daniel Pastor1, Jacob Izraelevitz3, Joel Burdick1, and Brett Kennedy3 Abstract—Aircraft that can launch ballistically and con- vert to autonomous, free-flying drones have applications in many areas such as emergency response, defense, and space exploration, where they can gather critical situa- tional data using onboard sensors. This paper presents a ballistically-launched, autonomously-stabilizing multirotor pro- totype (SQUID - Streamlined Quick Unfolding Investigation Drone) with an onboard sensor suite, autonomy pipeline, and passive aerodynamic stability. We demonstrate autonomous transition from passive to vision-based, active stabilization, confirming the multirotor’s ability to autonomously stabilize after a ballistic launch in a GPS-denied environment. I. INTRODUCTION Unmanned fixed-wing and multirotor aircraft are usually launched manually by an attentive human operator. Aerial systems that can instead be launched ballistically without op- erator intervention will play an important role in emergency response, defense, and space exploration where situational awareness is often required, but the ability to conventionally launch aircraft to gather this information is not available. Firefighters responding to massive and fast-moving fires could benefit from the ability to quickly launch drones Fig. 1: Launching SQUID: inside the launcher tube (left), through the forest canopy from a moving vehicle. This eye- deploying the arms and fins (center), and fully-deployed in-the-sky could provide valuable information on the status configuration (right). Note the slack in the development safety of burning structures, fire fronts, and safe paths for rapid tether and how the carriage assembly remains in the tube retreat.
    [Show full text]
  • Hezbollah and the Use of Drones As a Weapon of Terrorism
    Hezbollah’s Drones Hezbollah and the Use of Drones as a Weapon of Terrorism By Milton Hoenig The international terrorist group Hezbollah, driven by resistance to Israel, now regularly sends low flying drones into Israeli airspace. These drones are launched and remotely manned from the Hezbollah stronghold in Lebanon and presumably supplied by its patron and strategic partner, Iran. On the U.S. State Department’s list of terrorist organizations since 1995, Hezbollah has secured its presence in Lebanon through various phases. It established a strong social services network, and in 2008 it became the dominant political party in the Lebanese government and supported the Assad regime in the Syrian Civil War. Hezbollah’s drone flights into Israeli airspace Hezbollah’s first flight of an unmanned aerial vehicle (UAV) or drone, into Israeli airspace for reconnaissance purposes occurred in November 2004, catching Israeli intelligence off guard. A Mirsad-1 drone (an updated version of the early Iranian Mohajer drone used for reconnaissance of Iraqi troops during the 1980s Iran-Iraq War), flew south from Lebanon into Israel, hovered over the Western Galilee town of Nahariya for about 20 minutes and then returned to Lebanon before the Israeli air force could intercept it. Hezbollah leader Hassan Nasrallah boasted that the Mirsad could reach “anywhere, deep, deep” into Israel with 40 to 50 kilograms of explosives.1 One report at the time was that Iran had supplied Hezbollah with eight such drones, and over two years some 30 Lebanese operatives had
    [Show full text]
  • Unmanned Systems Roadmap: 2007-2032
    DEC 102007 MEMORANDUM FOR SECRETARIES OF THE MILITARY DEPARTMENTS CHAIRMAN OF THE JOINT CHIEFS OF STAFF CIllEF OF STAFF OF THE ARMY CIllEF OF NAVAL OPERAnONS CHIEF OF STAFF OF THE AIR FORCE COMMANDANT OF THE MARINE CORPS DIRECTOR, DEFENSE ADVANCED RESEARCH PROJECTS AGENCY SUBJECT: Unmanned Systems Roadmap This is the first edition ofthe integrated Office ofthe Secretary ofDefense Unmanned Systems Roadmap (2007-2032) which includes Unmanned Aircraft Systems, Unmanned Ground Systems, and Unmanned Maritime Systems. This roadmap provides Defense-wide vision for unmanned systems and related technologies. The Department will continue to promote a common vision for future unmanned systems by making this roadmap widely available to industry and our Allies, and updating it as transformational concepts emerge. Unmanned systems will continue to have a central role in meeting our country's diverse security needs, especially in the Global War on Terrorism. ~-- Under Secretary ofDefense Intelligence w1tt-:~/ mes E. Cartwright J G. Gri es General, USMC Assistant Secretary ofDefense Vice Chairman, Jo' t Chiefs ofStaff Networks and Information Integration Unmanned Systems Roadmap 2007-2032 Executive Summary Today’s military has seen an evolution in technology that is creating an entirely new capability to project power through the use of unmanned systems while reducing the risk to human life. The contributions of unmanned systems continue to increase. As of October 2006, coalition Unmanned Aircraft Systems (UASs), exclusive of hand-launched systems, had flown almost 400,000 flight hours in support of Operations Enduring Freedom and Iraqi Freedom, Unmanned Ground Vehicles (UGVs) had responded to over 11,000 Improvised Explosive Device (IED) situations, and Unmanned Maritime Systems (UMSs) had provided security to ports.
    [Show full text]
  • Where Should Humans Step Aside and Let The
    emotely piloted aircraft of human control alters the concept of University team sponsored by the Offi ce of such as the MQ-9 Reaper legitimate action. Naval Research. These robots could even and RQ-4 Global Hawk are Discomfort persists. “Drones are a “act as objective, unblinking observers manned by squadrons of technological step that further isolates the on the battlefi eld, reporting any unethical pilots and sensor operators on the ground. American people from military action,” behavior back to command,” they said in RFive or 10 years from now, however, law professor Mary L. Dudziak said, the report “Autonomous Military Robotics: that may no longer be the case, as full according to The New Yorker in a 2009 Risk, Ethics, and Design.” autonomy for air vehicles is well within article. The release of the November 2012 Taken to the extreme, autonomy theo- the Air Force’s technical reach. guidelines stirred calls for an executive retically enhances legitimacy. “Future According to USAF offi cials, artifi cial order stating that lethal and nonlethal generations may come to regard tactical intelligence and other technology advances attack with fully autonomous weapons warfare as properly the business of ma- will enable unmanned systems to make violates the law of war. chines and not appropriate for people at and execute complex decisions required Intriguingly, there is a vocal group on all,” noted Thomas K. Adams in a 2001 for full autonomy sometime in the decade the other side, too. These scientists see article for the US Army War College’s after 2015. autonomy as a means to reduce error journal Parameters, reprinted in 2011.
    [Show full text]