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Books on the topic 'Unmanned ground vehicles'

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Author: Grafiati
Published: 4 June 2021
Last updated: 21 February 2023

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1

Hebert, Martial H., Charles Thorpe, and Anthony Stentz, eds. Intelligent Unmanned Ground Vehicles. Boston, MA: Springer US, 1997. http://dx.doi.org/10.1007/978-1-4615-6325-9.

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2

National Research Council (U.S.). Committee on Army Unmanned Ground Vehicle Technology. and National Research Council (U.S.). Board on Army Science and Technology., eds. Technology development for Army unmanned ground vehicles. Washington, D.C: National Academies Press, 2002.

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3

Hebert, Martial H. Intelligent Unmanned Ground Vehicles: Autonomous Navigation Research at Carnegie Mellon. Boston, MA: Springer US, 1997.

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4

Introduction to unmanned systems: Air, ground, sea & space : technologies and commercial applications. [Phoenix, AZ]: Unmanned Vehicle University Press, 2013.

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5

R, Gerhart Grant, Shoemaker Chuck M, Gage Douglas W. 1945-, and Society of Photo-optical Instrumentation Engineers., eds. Unmanned ground vehicle technology V: 22-23 April, 2003, Orlando, Florida, USA. Bellingham, Wash: SPIE, 2003.

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6

Hume, David B. Integration of weaponized unmanned aircraft into the air-to-ground system. Maxwell Air Force Base, Ala: Air University Press, 2007.

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7

Neta, Beny. Benefit of sound cueing in combat simulation. Monterey, Calif: Naval Postgraduate School, 1993.

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8

Cersovsky, Donald D. Mathematical model and analysis of the Tactical Unmanned Ground Vehicle (TUGV) using computer simulation. Monterey, Calif: Naval Postgraduate School, 1993.

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9

Ni, Jun, Jibin Hu, and Changle Xiang. Design and Advanced Robust Chassis Dynamics Control for X-by-Wire Unmanned Ground Vehicle. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-031-01496-3.

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10

Dubanov, Aleksandr. Computer simulation in pursuit problems. ru: Publishing Center RIOR, 2022. http://dx.doi.org/10.29039/02102-6.

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Currently, computer simulation in virtual reality systems has a special status. In order for a computer model to meet the requirements of the tasks it models, it is necessary that the mathematical apparatus correctly describe the simulated phenomena. In this monograph, the simulation of pursuit problems is carried out. An adaptive modeling of the behavior of both pursuers and targets is carried out. An iterative calculation of the trajectories of the participants in the pursuit problem is carried out. The main attention is paid to the methods of pursuit and parallel rendezvous. These methods are taken as the basis of the study and are modified in the future. The scientific novelty of the study is the iterative calculation of the trajectories of the participants in the pursuit task when moving at a constant speed, while following the predicted trajectories. The predicted trajectories form a one-parameter network of continuous lines of the first order of smoothness. The predicted trajectories are calculated taking into account the restrictions on the curvature of the participant in the pursuit problem. The fact of restrictions on curvature can be interpreted as restrictions on the angular frequency of rotation of the object of the pursuit problem. Also, the novelty is the calculation of the iterative process of group pursuit of multiple targets, when targets are hit simultaneously or at specified intervals. The calculation of the parameters of the network of predicted trajectories is carried out with a curvature variation in order to achieve the desired temporal effect. The work also simulates the adaptive behavior of the pursuer and the target. The principle of behavior can be expressed on the example of a pursuer with a simple phrase: "You go to the left - I go to the left." This happens at each iteration step in terms of choosing the direction of rotation. For the purpose, the principle of adaptive behavior is expressed by the phrase: "You go to the left - I go to the right." The studies, algorithms and models presented in the monograph can be in demand in the design of autonomously controlled unmanned aerial vehicles with elements of artificial intelligence. The task models in the monograph are supplemented with many animated images, where you can see the research process. Also, the tasks have an implementation in a computer mathematics system and can be transferred to virtual reality systems if necessary.
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11

Gerhart, Grant R. Unmanned Ground Vehicle Technology 7. SPIE-International Society for Optical Engine, 2005.

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12

Committee on Army Unmanned Ground Vehicle Technology, Board on Army Science and Technology, National Research Council, and Division on Engineering and Physical Sciences. Technology Development for Army Unmanned Ground Vehicles. National Academies Press, 2002.

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13

Technology Development for Army Unmanned Ground Vehicles. Washington, D.C.: National Academies Press, 2002. http://dx.doi.org/10.17226/10592.

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14

Committee on Army Unmanned Ground Vehicle Technology, Board on Army Science and Technology, National Research Council, and Division on Engineering and Physical Sciences. Technology Development for Army Unmanned Ground Vehicles. National Academies Press, 2003.

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15

Committee on Army Unmanned Ground Vehicle Technology, Board on Army Science and Technology, National Research Council, and Division on Engineering and Physical Sciences. Technology Development for Army Unmanned Ground Vehicles. National Academies Press, 2003.

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16

Publisher, Brain Ants. 7-Step Engineering Design Guide Wheeled Robotic Vehicles: Unmanned Ground Vehicle. Independently Published, 2019.

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17

John, Aloimonos, ed. Visual navigation: From biological systems to unmanned ground vehicles. Mahwah, NJ: Lawrence Erlbaum Associates, 1997.

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18

Aloimonos, Yiannis. Visual Navigation: From Biological Systems to Unmanned Ground Vehicles. Taylor & Francis Group, 2015.

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19

Aloimonos, Yiannis. Visual Navigation: From Biological Systems to Unmanned Ground Vehicles. Taylor & Francis Group, 2013.

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20

Aloimonos, Yiannis. Visual Navigation: From Biological Systems to Unmanned Ground Vehicles. Taylor & Francis Group, 2013.

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21

Aloimonos, Yiannis. Visual Navigation: From Biological Systems to Unmanned Ground Vehicles. Taylor & Francis Group, 2013.

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22

Aloimonos, Yiannis. Visual Navigation: From Biological Systems to Unmanned Ground Vehicles. Taylor & Francis Group, 2013.

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23

Thorpe, Charles E., Martial H. Hebert, and Anthony Stentz. Intelligent Unmanned Ground Vehicles: Autonomous Navigation Research at Carnegie Mellon. Springer, 2013.

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24

Martial, Hebert, Thorpe Charles E, and Stentz Anthony, eds. Intelligent unmanned ground vehicles: Autonomous navigation research at Carnegie Mellon. Boston: Kluwer Academic Publishers, 1997.

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25

R, Gerhart Grant, Gunderson Robert W, Shoemaker Chuck M, and Society of Photo-optical Instrumentation Engineers., eds. Unmanned ground vehicle technology II: 24-25 April, 2000, Orlando, USA. Bellingham, Wash: SPIE, 2000.

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26

R, Gerhart Grant, Shoemaker Chuck M, Gage Douglas W. 1945-, and Society of Photo-optical Instrumentation Engineers., eds. Unmanned ground vehicle technology IV: 2-3 April, 2002, Orlando, [Florida] USA. Bellingham, Wash: SPIE, 2002.

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27

R, Gerhart Grant, Shoemaker Chuck M, Gage Douglas W. 1945-, and Society of Photo-optical Instrumentation Engineers., eds. Unmanned ground vehicle technology IV: 2-3 April, 2002, Orlando, [Florida] USA. Bellingham, Wash: SPIE, 2002.

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28

R, Gerhart Grant, Shoemaker Chuck M, Gage Douglas W. 1945-, and Society of Photo-optical Instrumentation Engineers., eds. Unmanned ground vehicle technology VI: 13-15 April, 2004, Orlando, Florida, USA. Bellingham, Wash: SPIE, 2004.

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29

Government, U. S., Department of Defense, and U. S. Army. 2009 - 2034 Unmanned Systems Integrated Roadmap - Unmanned Aircraft (UAS), Unmanned Aerial Vehicle (UAV), UGV Ground Vehicles, UMS Maritime Systems, Drones, Technologies, Current and Future Programs. Independently Published, 2017.

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30

Visual Navigation: From Biological Systems To Unmanned Ground Vehicles (Computer Vision Series). Lawrence Erlbaum, 1996.

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31

R, Gerhart Grant, Shoemaker Chuck M, and Society of Photo-optical Instrumentation Engineers., eds. Unmanned ground vehicle technology III: 16-17 April, 2001, Orlando, [Florida] USA. Bellingham, Washington: SPIE, 2001.

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32

(Editor), Martial H. Hebert, Charles E. Thorpe (Editor), and Anthony Stentz (Editor), eds. Intelligent Unmanned Ground Vehicles: Autonomous Navigation Research at Carnegie Mellon (The International Series in Engineering and Computer Science). Springer, 1996.

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33

Society of Photo-Optical Instrumentation Engineers (Corporate Author), Grant R. Gerhart (Editor), Robert W. Gunderson (Editor), and Chuck M. Shoemaker (Editor), eds. Unmanned Ground Vehicle Technology: 7-8 April 1999, Orlando, Florida (Proceedings of Spie--the International Society for Optical Engineering, V. 3693.). Society of Photo Optical, 1999.

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34

Wich, Serge A., and Lian Pin Koh. Typology and anatomy of drones. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198787617.003.0002.

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In this chapter we discuss the typology of drones that are currently being used for different kinds of environmental and conservation applications. Drones are also commonly known variously as Remotely Piloted Aircraft Systems (RPAS), Unmanned Aerial Vehicles (UAV), and Unmanned Aircraft Systems (UAS). We focus on the most popular aircraft types including multirotor (of various configurations), fixed wing, and hybrid ‘vertical-take-off-and-landing’ (VTOL) craft, and briefly discuss the relative pros and cons of each type. We also broadly discuss the essential components common to all remotely piloted aircraft systems, including the power source, flight controller (or autopilot), and ground control station.
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35

Military, U. S., Defense Science Board, and Department of Defense. Role of Autonomy in DOD Systems - Reports on Unmanned Aerial Vehicles (UAV), Robotics, Teleoperation, Haptics, Centibot, Remote Presence, UxV, DARPA Research, and Space and Ground Systems. Independently Published, 2017.

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36

Adwitya, Adwitya. Unmanned Ground Vehicle Using a GSM Network. Notion Press, 2020.

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37

Darpa. Rsta: Reconnaissance, Surveillance, and Target Acquisition for the Unmanned Ground Vehicle. Morgan Kaufmann Publishers, 1997.

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38

Ma, Yue. Dynamics and Advanced Motion Control of Unmanned Ground off-Road Vehicle. Elsevier Science & Technology, 2020.

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39

NI, Jun, Jibin Hu, and Changle Xiang. Design and Advanced Robust Chassis Dynamics Control for X-by-Wire Unmanned Ground Vehicle. Morgan & Claypool Publishers, 2018.

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40

Ziang, Changle, Jun NI, and Jibin Hu. Design and Advanced Robust Chassis Dynamics Control for X-By-Wire Unmanned Ground Vehicle. Springer International Publishing AG, 2018.

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41

NI, Jun, Jibin Hu, and Changle Xiang. Design and Advanced Robust Chassis Dynamics Control for X-by-Wire Unmanned Ground Vehicle. Morgan & Claypool Publishers, 2018.

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42

Khajepour, Amir, Jun NI, Jibin Hu, and Changle Xiang. Design and Advanced Robust Chassis Dynamics Control for X-By-Wire Unmanned Ground Vehicle. Morgan & Claypool Publishers, 2018.

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43

NATO Reference Mobility Model (NRMM) Modeling of the DEMO III experimental Unmanned Ground Vehicle (XUV). Storming Media, 1999.

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44

Target Acquisition and Engagement from an Unmanned Ground Vehicle: The Robotics Test Bed of Demo 1. Storming Media, 1996.

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45

Fontgalland, Glauco. Smart Systems: Theory and Advances. Amplla Editora, 2022. http://dx.doi.org/10.51859/amplla.sst631.1122-0.

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This book aims to highlight the strength and state-of-art of some techniques and methods applied to intelligent systems. Rather to cover the variety of techniques and methods available in the literature, which is out of scope of this book, it focuses on those consolidated and applied and on those with high potential of implementation to smart systems. This book has fourteen chapters covering abroad range of topics in communications. The first three chapters are devoted to state-of-art and review papers on planar filters, unmanned aerial vehicles (UAV), negative group delay, nanoclusters, and tunable lights, while the remain chapters cover specific topics such as smart monitoring, V2I, high-speed links, RF and Optical sensors, composite material, metamaterial, energy harvesting, radar, SWIPT, and electromagnetic sources.
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46

Department of Defense. Counter Unmanned Aerial Vehicle (UAV) Solutions for the Joint Force - Aerial Threat of Remote Controlled Quadcopters and Drones, Black Dart Exercises, Jamming, Lasers, and Ground-To-Air Missiles. Independently Published, 2019.

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