Intelligent Systems, Control and Automation: Science and Engineering Kenzo Nonami Muljowidodo Kartidjo Kwang-Joon Yoon Agus Budiyono Editors Autonomous Control Systems and Vehicles Intelligent Unmanned Systems Autonomous Control Systems and Vehicles International Series on INTELLIGENT SYSTEMS, CONTROL AND AUTOMATION: SCIENCE AND ENGINEERING VOLUME 65 Editor Professor S G Tzafestas, National Technical University of Athens, Greece Editorial Advisory Board Professor P Antsaklis, University of Notre Dame, Notre Dame, IN, USA Professor P Borne, Ecole Centrale de Lille, Lille, France Professor D.G Caldwell, University of Salford, Salford, UK Professor C.S Chen, University of Akron, Akron, Ohio, USA Professor T Fukuda, Nagoya University, Nagoya, Japan Professor S Monaco, University La Sapienza, Rome, Italy Professor G Schmidt, Technical University of Munich, Munich, Germany Professor S.G Tzafestas, National Technical University of Athens, Athens, Greece Professor F Harashima, University of Tokyo, Tokyo, Japan Professor N.K Sinha, McMaster University, Hamilton, Ontario, Canada Professor D Tabak, George Mason University, Fairfax, Virginia, USA Professor K Valavanis, University of Denver, Denver, USA For further volumes: http://www.springer.com/series/6259 Kenzo Nonami • Muljowidodo Kartidjo Kwang-Joon Yoon • Agus Budiyono Editors Autonomous Control Systems and Vehicles Intelligent Unmanned Systems Editors Kenzo Nonami Graduate School and Faculty of Engineering Chiba University Chiba, Japan Kwang-Joon Yoon Konkuk University Seoul, Korea, Republic of (South Korea) Muljowidodo Kartidjo Center for Unmanned System Studies Institute of Technology Bandung Bandung, Indonesia Agus Budiyono Department of Aerospace and Information Engineering, Smart Robot Center Konkuk University Seoul, Korea, Republic of (South Korea) ISBN 978-4-431-54275-9 ISBN 978-4-431-54276-6 (eBook) DOI 10.1007/978-4-431-54276-6 Springer Tokyo Heidelberg New York Dordrecht London Library of Congress Control Number: 2013936546 # Springer Japan 2013 This work is subject to copyright All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed Exempted from this legal reservation are brief excerpts in connection with reviews or scholarly analysis or material supplied specifically for the purpose of being entered and executed on a computer system, for exclusive use by the purchaser of the work Duplication of this publication or parts thereof is permitted only under the provisions of the Copyright Law of the Publisher’s location, in its current version, and permission for use must always be obtained from Springer Permissions for use may be obtained through RightsLink at the Copyright Clearance Center Violations are liable to prosecution under the respective Copyright Law The use of general descriptive names, registered names, trademarks, service marks, etc in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use While the advice and information in this book are believed to be true and accurate at the date of publication, neither the authors nor the editors nor the publisher can accept any legal responsibility for any errors or omissions that may be made The publisher makes no warranty, express or implied, with respect to the material contained herein Printed on acid-free paper Springer is part of Springer Science+Business Media (www.springer.com) Preface The International Conference on Intelligent Unmanned Systems (ICIUS) 2011 was organized by the International Society of Intelligent Unmanned Systems (ISIUS) and locally by the Center for Bio-Micro Robotics Research at Chiba University, Japan The event was the 7th conference continuing from previous conferences held in Seoul, Korea (2005, 2006), Bali, Indonesia (2007), Nanjing, China (2008), Jeju, Korea (2009), and Bali, Indonesia (2010) ICIUS2011 focused on both theory and application, primarily covering the topics of robotics, autonomous vehicles, intelligent unmanned technologies, and biomimetics We invited seven keynote speakers who dealt with related state-of-the-art technologies including unmanned aerial vehicles (UAVs) and micro air vehicles (MAVs), flapping wings (FWs), unmanned ground vehicles (UGVs), underwater vehicles (UVs), bio-inspired robotics, advanced control, and intelligent systems, among others Simultaneously, the exhibition and demonstrations and the panel discussion were arranged to cover advanced relevant technologies in this field The aim of the conference was to stimulate interactions among researchers active in the areas pertinent to intelligent unmanned systems This special-interest conference successfully attracted 113 papers internationally, covering the following topics: • Unmanned systems: UAVs, MAVs, unmanned marine vehicles (UMVs), underwater vehicles (UVs), multi-agent systems, UGVs, blimps, swarm intelligence, autonomous flying robots (AFRs), and flapping robots (FRs) • Robotics and biomimetics: smart sensors, design and applications of MEMS/ NEMS, intelligent robot systems, evolutionary algorithms, control of biological systems, biological learning control systems, neural networks, and bioinformatics • Control and computation: distributed and embedded systems, embedded intelligent control, complex systems, pervasive computing, discrete event systems, hybrid systems, networked control systems, delay systems, identification and estimation, nonlinear systems, precision motion control, control applications, computer architecture and VLSI, signal/image and multimedia v vi Preface processing, software-enabled control, real-time operating systems, architecture for autonomous systems, software engineering for real-time systems, and real-time data communications • Context-aware computing intelligent systems: soft computing, ubiquitous computing, distributed intelligence, and distributed/decentralized intelligent control ICIUS2011 was strongly supported by IEEE, the Japan Society of Mechanical Engineers (JSME), the Society of Instrument and Control Engineers (SICE), the Institute of Systems, Control and Information Engineers (ISCIE), Robotics Society of Japan (RSJ), the Japan Society for Aeronautical and Space Sciences (JSASS), Japan UAV Association (JUAV), the Chiba Convention Bureau and International Center, and the NSK Mechatronics Technology Advancement Foundation, Chiba University On behalf of the organization committee, we would like to express our appreciation for the support provided by those organizations We would also like to use this opportunity to thank all individuals and organizations who contributed to making ICIUS2011 successful and memorable This book is a collection of excellent papers that were updated after presentation at ICIUS2011 The evaluation committee of ICIUS2011 finally decided to select a total of 21 of those papers including the keynote papers All papers that form the chapters of this book were reviewed and revised from the perspective of advanced relevant technologies in the field The book is organized into four parts, which reflect the research topics of the conference themes: Part 1: Trends in Intelligent and Autonomous Unmanned Systems Part 2: Trends in Research Activities of UAVs and MAVs Part 3: Trends in Research Activities of UGVs Part 4: Trends in Research Activities of Underwater Vehicles, Micro Robots, and Others One aim of this book is to stimulate interactions among researchers in the areas pertinent to intelligent unmanned systems of UAV, MAV, UGV, USV, and UV, namely, autonomous control systems and vehicles Another aim is to share new ideas, new challenges, and the authors’ expertise on critical and emerging technologies The book covers multifaceted aspects of intelligent unmanned systems The editors hope that readers will find this book not only stimulating but also useful and usable in whatever aspect of unmanned system design in which they may be involved or interested The editors would like to express their sincere appreciation to all the contributors for their cooperation in producing this book The contribution from the keynote speakers is gratefully acknowledged, and all authors are to be congratulated for their efforts in preparing such excellent chapters Finally, the publisher, Springer, and most importantly Ms Y Sumino and Ms T Sato have been extremely supportive in the publication of this book We especially want to thank Ms Sumino and Ms Sato for their contribution Chiba, Japan Bandung, Indonesia Seoul Korea, Republic of (South Korea) Seoul Korea, Republic of (South Korea) Kenzo Nonami Muljowidodo Kartidjo Kwang-Joon Yoon Agus Budiyono Contents Part I Flight Demonstrations of Fault Tolerant Flight Control Using Small UAVs Shinji Suzuki, Yuka Yoshimatsu, and Koichi Miyaji Unmanned Aerial and Ground Vehicle Teams: Recent Work and Open Problems Steven L Waslander 21 Cognitive Developmental Robotics: from Physical Interaction to Social One Minoru Asada 37 Part II Trends of Intelligent and Autonomous Unmanned Systems Trends on Research Activities of UAVs and MAVs Towards a Unified Framework for UAS Autonomy and Technology Readiness Assessment (ATRA) Farid Kendoul 55 Control Scheme for Automatic Takeoff and Landing of Small Electric Helicopter Satoshi Suzuki 73 Evaluation of an Easy Operation System for Unmanned Helicopter Masafumi Miwa, Shouta Nakamatsu, and Kentaro Kinoshita 85 Control of Ducted Fan Flying Object Using Thrust Vectoring Masafumi Miwa, Yuki Shigematsu, and Takashi Yamashita 97 vii viii Contents Circular Formation Control of Multiple Quadrotor Aerial Vehicles 109 M Fadhil Abas, Dwi Pebrianti, Syaril Azrad, D Iwakura, Yuze Song, and K Nonami Decentralised Formation Control of Unmanned Aerial Vehicles Using Virtual Leaders 133 Takuma Hino and Takeshi Tsuchiya 10 Aerodynamics and Flight Stability of Bio-inspired, Flapping-Wing Micro Air Vehicles 145 Hao Liu, Xiaolan Wang, Toshiyuki Nakata, and Kazuyuki Yoshida 11 Development and Operational Experiences of UAVs for Scientific Research in Antarctica 159 S Higashino, M Funaki, N Hirasawa, M Hayashi and S Nagasaki 12 Circularly Polarized Synthetic Aperture Radar Onboard Unmanned Aerial Vehicle (CP-SAR UAV) 175 Josaphat Tetuko Sri Sumantyo Part III Trends on Research Activities of UGVs 13 Modeling and Control of Wheeled Mobile Robots: From Kinematics to Dynamics with Slipping and Skidding 195 Makoto Yokoyama 14 Consideration of Mounted Position of Grousers on Flexible Wheels for Lunar Exploration Rovers to Traverse Loose Soil 211 Kojiro Iizuka 15 Optimal Impedance Control with TSK-Type FLC for Hard Shaking Reduction on Hydraulically Driven Hexapod Robot 223 Addie Irawan, Kenzo Nonami, and Mohd Razali Daud 16 LRF Assisted Autonomous Walking in Rough Terrain for Hexapod Robot COMET-IV 237 M.R Daud, K Nonami, and A Irawan 17 Walking Directional Control of Six-Legged Robot by Time-Varying Feedback System 251 H Uchida and N Shiina Contents Part IV ix Trends on Research Activities of Underwater Vehicle, Micro Robot and Others 18 Design and Operation Analysis of Hybrid AUV 267 K Muljowidodo, Sapto Adi Nugroho, and Nico Prayogo 19 Ultrasound Energy Transmission for WaFLES-Support Intra-abdominal Micro Robots 279 Takuya Akagi, David Gomez, Jose Gonzalez, Tatsuo Igarashi, and Wenwei Yu 20 Simulation of Supercavitating Flow Accelerated by Shock 291 B.C Khoo and J.G Zheng 21 Dynamics of Vortices Shed from an Elastic Heaving Thin Film by Fluid–Structure Interaction Simulation 299 Tetsushi Nagata, Masaki Fuchiwaki, and Kazuhiro Tanaka Index 311 Chapter 21 Dynamics of Vortices Shed from an Elastic Heaving Thin Film by Fluid–Structure Interaction Simulation Tetsushi Nagata, Masaki Fuchiwaki, and Kazuhiro Tanaka Abstract The flow field around a moving body is treated as a fluid–structure interaction, and such phenomena consist of a series of moving elastic deformations of the body, vortex generation, growth, and development In particular, the flow fields around thin materials have attracted attention due to their importance with respect to the development of micro air vehicles, for example In this paper, we simulate the fluid–structure interaction of flow fields around an elastic heaving thin film using ANSYS 12.1/ANSYS CFX 12.1 The purpose of this study is to clarify the development of vortex flow structures in the wake of elastic heaving thin films Keywords Fluid-structure interaction • Heaving thin film 21.1 Introduction The flow field around a moving body is treated as a fluid–structure interaction (FSI), which is a series of phenomena that range from the elastic deformation of a body to vortex generation/growing/development A wake structure of vortices changes three-dimensionally and dramatically Therefore, the dynamics of vortices shed from a moving body become complicated, and it is difficult to visualize and evaluate three-dimensional vortex flow fields experimentally and numerically T Nagata (*) Graduate School of Computer Science and Systems Engineering, Kyushu Institute of Technology, 680-4 Kawazu, Iizuka-City, Fukuoka 820-8502, Japan e-mail: nagata@vortex.mse.kyutech.ac.jp M Fuchiwaki • K Tanaka Department of Mechanical Information Science and Technology, Kyushu Institute of Technology, 680-4 Kawazu, Iizuka-City, Fukuoka 820-8502, Japan K Nonami et al (eds.), Autonomous Control Systems and Vehicles, Intelligent Systems, Control and Automation: Science and Engineering 65, DOI 10.1007/978-4-431-54276-6_21, # Springer Japan 2013 299 300 T Nagata et al because of the difficulties involved in measuring the flow field for experiment and the coupling approach problem for the numerical simulation Thus far, flow fields with elastic deformation have been clarified primarily through numerical methods One-way coupled analyses that consider small structural deformation [1] and coupled analyses, for which the elastic deformation is expressed through functions [2], have been performed However, the influence of fluid behavior [1] or structural deformation [2] was not considered in these methods Therefore, actual phenomena are not reproduced by these approaches However, it is difficult to develop a bi-directional coupling method, such as meshing, convergence, and data passing between fluid and structure in the case of considering a large structural deformation Stanford [3] investigated the flow field around the moving wing of a micro air vehicle (MAV) by a bi-directional coupling analysis that strictly considers fluid–structure interaction The wing deformed slightly due to the fluid force and its deformation effects were fed back to the flow field However, the deformation was only % for the wing chord length Therefore, thus far, bi-directional coupled problems, in which large deformations are considered, have not been discussed sufficiently An MAV and a micro flapping robot with an insect flight mechanism are being actively developed, and the importance of the elastic deformation of the thin wing has gradually been clarified [4] Thin materials easily deform due to small motions and fluid pressure around the body because of the small second moment of area Flow fields around thin film materials are investigated for paper webs in a printing press [5] and are treated as important in developing an MAV for optimized design of a wing model However, thin films have significant bi-directional impacts on fluid force and structure deformation, and it is difficult to clarify these strong coupling phenomena Flow fields around a thin film have also been clarified numerically [6] However, most methods involve one-way coupling analysis and so cannot simulate actual phenomena Therefore, it is important to clarify the flow fields around a thin film using a bi-directional coupling method that considers interactions between a fluid and structure In a previous study, we experimentally clarified the vortex structures behind the heaving elastic airfoil and unsteady dynamic forces [7] We also previously performed a bi-directional coupling simulation of fluid–structure interactions of a flow field around an elastic heaving airfoil using ANSYS 11.0/ANSYS-CFX 11.0, and the obtained simulation results agreed well with the experimental results for flow fields and the characteristics of dynamic forces [8] Consequently, we believe that a simulation method would be a useful tool for clarifying elastic effects and coupling phenomena, where interactions between fluid and structure are considered In this paper, we simulate the FSI of a flow field around an elastic heaving thin film with deformation using ANSYS 12.1/ANSYS-CFX 12.1 The purpose of this study is to clarify the dynamics of vortices shed from a heaving thin film and to clarify the effects of elasticity on the vortices formed in a wake as well as the structures of an elastic heaving thin film 21 Dynamics of Vortices Shed from an Elastic Heaving Thin Film 21.2 301 Materials and Methods 21.2.1 Thin Film Model An elastic thin film is formed into a wing [9], which is used as a micro flapping robot, as shown in Fig 21.1 The chord c, span length l, and thickness h are 80, 120, and 0.035 mm, respectively The chord and span directions are fixed with the frame The non-deformation condition and the heaving motion of Eq (21.1) are applied to the part of chord indicated by the solid line The frame of the leading edge indicated that the dashed line is passively deformed due to the heaving motion The Strouhal number is defined by Eq (21.2) y ẳ a sin2ftị St ẳ (21.1) 2af V0 (21.2) 21.2.2 Numerical Method In this study, we performed a numerical analysis of the flow field around an elastic thin film through a fluid–structure coupled analysis The governing equations of the fluid are the equations of continuity and the Navier–Stokes equation given by Eqs (21.3) and (21.4), respectively, and the finite volume method (FVM) is used for the discretization procedure On the other hand, the governing equation of the structural part is the constitutive equation given by Eq (21.5), and the finite element method (FEM) is used for the discretization procedure The number of divisions for the thin film thickness is one The height of the first lattice point is approximately 0.4% of the chord length c The y+ is less than 30 Therefore, the resolution of the interface is not sufficient For the boundary surface of the thin film, an interface that transmits pressure and displacement data is defined Main flow Passively deformed Tip Heaving z/l = 0.6 y Fig 21.1 Thin film configuration z Thin film x 302 T Nagata et al Table 21.1 Simulation condition of the thin film E ν ρ fn Motion Amplitude 2.0 GPa 0.3 1,000 kg/m3 2.3 Hz Heaving 0.012 m Frequency Analysis Mesh Elements Iteration NS Convergence 5.0 Hz Nonlinear Hexa 1.6  103 15 104 Table 21.2 Simulation condition of the fluid region Fluid Re St Mesh Nodes Turbulence Air 103 0.24 Hexa, tetra  105 k–ω Iteration NF Convergence Inlet Outlet Wall 15 104 0.5 m/s Pa Symmetry for the thin film surface Tables 21.1 and 21.2 show the properties of the elastic thin film, the analysis conditions, and fluid analysis conditions The time step size is Δt ¼ 0.001 s and we calculated heaving motion cycles rU ẳ0 @U ỵ r  U  Uị ẳ rp ỵ r  rU ỵ rUịT ị @t ẵMX ỵ ẵCX_ ỵ ẵKX ẳ F (21.3) (21.4) (21.5) 21.2.3 Coupling Method In the proposed method, the interaction between a fluid and a structure is considered for a bi-directional coupling simulation We apply a decoupled solver, which is referred to as the weak coupled method, in which the governing equations of the fluid and structural regions are calculated independently [7] Although this method has problems with respect to calculation time, convergence, and mapping of the interface data, the governing equations are calculated precisely Therefore, data transfer of physical quantities related to the fluid–structure interface can be transferred adequately As a result, actual phenomena related to fluid and structural regions can be treated strictly This coupling analysis consists of three regions: the fluid analysis region, the structural analysis region, and the mesh movement calculating region 21 Dynamics of Vortices Shed from an Elastic Heaving Thin Film 303 Fig 21.2 Displacement of the heaving thin film Fig 21.3 Trailing edge displacement of the heaving thin film : Driving motion : Displacement at tip : Displacement at z/l=0.6 y/a 1.0 0.0 –1.0 0.0 0.5 t/T 1.0 Moreover, interpolations are performed when the fluid pressure and the structural displacement are transferred on the interface because of the independence of the meshing between the fluid and the structural region These three calculation processes are performed and referred to as a step 21.2.4 Displacement of the Heaving Thin Film Figures 21.2 and 21.3 show the displacement for the heaving direction of the heaving thin film The contours in Fig 21.2 indicate the displacement The horizontal and vertical axes in Fig 21.3 indicate the heaving cycle t/T and the heaving displacement y/a, respectively The black, red, and blue lines indicate the displacement of the driving motion, the displacement at the tip, and the displacement at the z/l ¼ 0.6, respectively As shown in Figs 21.2 and 21.3, the displacement at the tip in the leading edge is large around the top and the bottom dead positions due to the inertia force generated by the heaving motion and the fluid pressure acting on the surface of the heaving thin film The thin film at z/l ¼ 0.6 also deforms significantly, where the 304 T Nagata et al displacement reaches a maximum value that is 1.45 times larger than heaving amplitude Therefore, the trailing edge displacement is larger than the leading edge displacement Therefore, the paper part deforms by compulsion due to the compelling force of following the rigidity material 21.3 Results and Discussion 21.3.1 Iso-Surface of Vorticity Around the Thin Plate and Thin Film Figures 21.4 and 21.5 show the iso-surfaces of vorticity up to 25 1/s that is formed around the heaving thin plate and the thin film, respectively Figures 21.4a and 21.5a show the instantaneous vortex flow structure around the moving body at t/T ¼ 0.00 Figures 21.4 and 21.5b–d show the flow fields developed in the wake at t/T ¼ 0.15, 0.35, and 0.55, respectively Fig 21.4 Iso-surfaces of vorticity around the heaving thin plate (a) Around the thin plate at t/T ¼ 0.00, (b) t/T ¼ 0.15, (c) t/T ¼ 0.35, and (d) t/T ¼ 0.55 21 Dynamics of Vortices Shed from an Elastic Heaving Thin Film 305 Fig 21.5 Iso-surfaces of vorticity around the heaving thin film (a) Around thin plate at t/T ¼ 0.00, (b) t/T ¼ 0.15, (c) t/T ¼ 0.35, and (d) t/T ¼ 0.55 As shown in Fig 21.4a, the three-dimensional complex vortex structure is formed around the heaving thin plate because of the rolled-up vortices at the wing chord, the leading edge, and the trailing edge As shown in Fig 21.4b, the vortex structure in the wake at t/T ¼ 0.15 is rarely different from the structure at t/T ¼ 0.0 Moreover, as shown in Fig 21.4c, d, when the heaving thin film moves downward, the vortex structure differs only slightly from the before-vortex flow field and developed in the wake Therefore, complicated vortex structures are formed behind the thin plate, even without elastic deformation On the other hand, the thin film forms a vortex flow with both heaving motion and elastic deformation, as shown in Fig 21.5 As shown in Fig 21.5a, the vortices are developed behind the thin film and have an extremely similar structure to that of the thin plate The vortex structure at t/T ¼ 0.15 in Fig 21.5b is also rarely different from the vortex behavior in Fig 21.5a Moreover, the vortex structure remains unchanged and is developed behind the thin film in Fig 21.5c, d Although small differences in the wake structure can be observed between the thin plate and the film, it is difficult to understand the effect of the elasticity on the three-dimensional vortex flow Therefore, three-dimensional vortex structures are formed behind the thin film and the development in the wake is similar to the behavior of the flow fileds in the thin plate regardless of the elastic deformation 306 T Nagata et al Fig 21.6 Vorticity contours of the wing section around the heaving thin plate at t/T ¼ 0.35: (a) z/l ¼ 0.3 and (b) z/l ¼ 0.6 21.3.2 Vorticity Contours Around the Heaving Thin Plate and Film Figures 21.6 and 21.7 show the vorticity contours around the thin plate and the thin film at t/T ¼ 0.35, respectively In the figures, (a) and (b) show the contours of the wing section at z/l ¼ 0.3 and 0.6 of the chord, respectively As shown in Fig 21.6a, the vortices are rolled up from the leading and the trailing edge of the thin plate, and the vortices that rolled up at the trailing edge are developed in the wake In particular, a narrow vertical interval of vortices is found behind the thin plate, and these vortices are arranged in a straight line Moreover, as shown in Fig 21.6b at z/l ¼ 0.6, the vortex flow pattern behind the thin plate is also similar to the results at z/l ¼ 0.3 Therefore, the vortices behind the thin plate tend to be arranged in lines 21 Dynamics of Vortices Shed from an Elastic Heaving Thin Film 307 Fig 21.7 Vorticity contours of the wing section around the heaving thin film at t/T ¼ 0.35: (a) z/l ¼ 0.3 and (b) z/l ¼ 0.6 As shown in Fig 21.7a at z/l ¼ 0.3, the leading edge vortex is rolled up just like for the thin plate, and the trailing edge vortex is also rolled up with elastic deformation A thrust-producing vortex street, which is a reverse Karman vortex street, is formed behind the heaving thin film This is because the vortices rolled up widely around the top and bottom dead positions as a result of the elastic deformation Moreover, a clear thrust-producing vortex street also is observed in the crosssection at z/l ¼ 0.6 due to the large elastic deformation in Fig 21.7b Therefore, although the three-dimensional vortex structures are formed intricately around both the thin plate and the thin film, these cross-sectional flow patterns are clearly different with respect to the alignment of the vortices Moreover, the thrustproducing vortex street is clearly formed only behind the thin film 308 T Nagata et al Fig 21.8 Dynamic thrust acting on the heaving thin plate and thin film for one heaving cycle 0.3 : Thin plate : Thin film CT 0.2 0.1 0.0 –0.1 0.0 0.5 t/T 1.0 21.3.3 Dynamic Thrust Acting on the Heaving Thin Plate and Thin Film Figure 21.8 shows the dynamic thrust acting on the heaving thin plate and the thin film The horizontal and vertical axes indicate the heaving cycle and the thrust coefficient, respectively The black and red lines indicate the results for the thin plate and the thin film, respectively As shown in Fig 21.8, clear differences in the dynamic thrust acting on the thin plate and on the thin film are found The dynamic thrust of the thin plate is extremely small and the average value during one cycle is 2.8  103 Therefore, the dynamic thrust is not generated for the thin plate because a thrust-producing vortex street is not formed behind the thin plate in Fig 21.6 On the other hand, the dynamic thrust of the thin film is much larger than that of the thin plate and reaches a maximum at approximately t/T ¼ 0.3, when the elastic deformation also reaches the maximum That is why the vortices are widely rolled up vertically from the trailing edge by the large elastic deformation, and the clear thrust-producing vortex street is formed behind the heaving thin film in Fig 21.7 Consequently, the heaving thin film can achieve a large dynamic thrust due to the elastic deformation 21.4 Conclusions A heaving thin film can roll up strong vortices on the trailing edge due to elastic deformation, and the scale of vortex structure behind the thin film becomes slightly larger than that of a heaving thin plate Although the effect of elasticity has a small impact on the three-dimensional vortex structure, the thin film deform significantly However, a clear thrust-producing vortex street is formed behind the thin film against forming the straight line of vortices behind the thin plate As a result, the dynamic thrust of the thin film is also larger than that of the thin plate 21 Dynamics of Vortices Shed from an Elastic Heaving Thin Film 309 References Erath W et al (1999) Modeling the fluid structure interaction produced by a waterhammer during shutdown of high-pressure pumps Nucl Eng Design 193:283–296 Maio J-M et al (2006) Effect of flexure on aerodynamic propulsive efficiency of flapping flexible airfoil J Fluid Struct 22:401–419 Stanford B et al (2008) Fixed membrane wings for micro air vehicles: experimental characterization, numerical modeling, and tailoring Prog Aerosp Sci 44:258–294 Regan W (2006) 10th international conference on the simulation and synthesis M.I.T., Cambridge, pp 241–247 Kulachenko A et al (2007) Modeling the dynamical behavior of paper web Part II Comput Struct 85:148–157 Huang W-X et al (2007) Simulation of flexible filaments in a uniform flow by the immersed boundary method J Comput Phys 226:2206–2228 Fuchiwaki M et al (2009) Detailed wake structure behind an elastic airfoil J Fluid Technol 4(2):391–400 Nagata T et al (2010) Study on vortex flow structure and dynamic forces on an elastic heaving airfoil by fluid-structure interaction simulation ICJWSF, Cincinnati Fuchiwaki M et al (2009) Characteristics of butterfly wings motions and their application to micro flight robot AIAA, Florida Index A Acceleration feedback, 74, 76–82 Active inter modal mapping (AIM), 41 Adaptability, 38 ADS See Air data system (ADS) Aerodynamic interference, 143 Aerodynamics, 145–156 Aileron, 8, AIM See Active inter modal mapping (AIM) Aircraft equations, Air data system (ADS), 13 Air flow, 111, 112, 116 Air-ground networks, 28 Airspeed, 13 AL See Autonomy level (AL) Angle of attack, 13 Antarctica, 159–173 Artificial muscles, 40 ASD See Autsitic spectrum disorder (ASD) ATRA See Autonomy and technology readiness assessment (ATRA) Automatic flight beyond visual range, 68 Automatic takeoff and landing, 73–83 Autonomous control, 74 Autonomous landings, 23 Autonomous unmanned aircraft systems, 55 Autonomous underwater vehicle (AUV), 267–277 Autonomy, 38 Autonomy and technology readiness assessment (ATRA) framework, 63 graph, 67 Autonomy characterization, 57 Autonomy level (AL), 55, 63 Autonomy-related terminology, 59 Autopilot, 15 Autsitic spectrum disorder (ASD), 50 AUV See Autonomous underwater vehicle (AUV) B Back propagation, 43 Backstepping, 195, 199, 201, 203, 204 Bank angle, 7, Balloon, 161, 163, 164, 166–168, 172 Behavior observation, 38 Biped walking, 40 Body height, 246 Body image, 37, 41 Body mass coordination, 233 Body posture, 233 Body representation, 38 Brain imaging studies, 50 Buoyancy engine, 270, 273, 275 C CAECs See Critical autonomy-enabling components (CAECs) Center of body, 225 Center of mass (CoM), 227, 229 Centripetal force, 111, 120 Circular motion, 109, 111, 120, 121, 125 Clap-and-fling, 146, 147, 153 Closed area, 110 Cognitive development, 50 Cognitive developmental robotics, 37 CoM See Center of mass (CoM) COMET-IV, 238 Communication failures, 137 K Nonami et al (eds.), Autonomous Control Systems and Vehicles, Intelligent Systems, Control and Automation: Science and Engineering 65, DOI 10.1007/978-4-431-54276-6, # Springer Japan 2013 311 312 Computational model, 38 Constraints on the interaction, 37 Coordinated control, 26 Coordinated landing, 24, 26 Correspondence, 34 Critical autonomy-enabling components (CAECs), 67 Crossing-over, 238, 243, 246 CSIRO Autonomous Helicopter, 68 D 3D coordinate system, 240 Decentralised, 133 Degree of freedom, 224 Developmental disorders, 50 3D occupancy grid mapping, 241 Drivability map, 33 3D simulation, 252, 257–262 Ducted fan, 13, 97–104, 106, 107 Dynamic force, 300 E Easy operation system, 85, 88 Effect of grousers, 214 Elastic effect, 216 Elastic moving airfoil, 300 Emotional facial expressions, 46 Empathy, 38 Energy transmission, 279–283, 288 F Fault tolerant flight control (FTFC), 3, 11 Feedback controller, Feedback error learning (FEL), Feedforward signal, FEL See Feedback error learning (FEL) Fetus development, 40 Fetus simulation, 50 Field-programmable gate array (FPGA), 75, 81 Final-phase, 239 First-phase, 239 Fixed-wing UAV, 22 Flapping, 145–156 Flexible wheels, 212 Flexure of flexible wheel, 218 Flight automation, control, 162, 163, 165, 166 Index demonstration, 17 safety, 17 stability, 145–156 tests, 15 Flocking, 28 Fluid–structure interaction, 299–308 fMRI, 49 Formation control, 24, 27, 33, 133 Formation flight, 133 FPGA See Field-programmable gate array (FPGA) Friction angle of soil, 215 FTFC See Fault tolerant flight control (FTFC) Fuzzy logic control, 224 G Game controller, 85–89, 93, 95 Geomagnetic survey, 160, 161, 169, 172 Global positioning system (GPS), Graphical user interface (GUI), 115, 116 Grid map, 244 Ground effect, 27, 111–113 Ground pilot, 15 Ground station, 164, 166, 167 Grousers, 212 GUI See Graphical user interface (GUI) H Hard shaking, 223–235 Hebbian learning, 41 Helicopter air flow, 112 Homogeneous model, 293, 295 Hybrid autonomous underwater vehicle (HAUV), 267–277 I Image-based visual servoing, 25 Imitation, 38 Impedance control, 223–235 Induced drag, 133 Information structuring, 38 Inner-outer loop, 118 Inspection, 24 Interaction model, 213 Internal mechanism, 38 Internal state, 46 Intuitive parenting, 37, 41 Inverse model, Isentropic cavitation model, 295 Index J Jacobian, 41 Joint attention, 38 JX-1, 175, 177–179, 183, 189, 190 K Kalman filter, 76, 77, 79–81 L Leader–follower, 135 Leader–follower formation control (LFFC), 127, 128 Leader–follower strategy, 110, 114, 120, 125, 131 Learning rate, Left-handed circular polarization (LHCP), 177, 178, 181, 183, 184, 190 Leg swing trajectory, 242 LFFC See Leader–follower formation control (LFFC) LHCP See Left-handed circular polarization (LHCP) Limbs, 211 Line tracking, Localization, 34 Loose soil, 211–220 Lunar exploration rovers, 211–220 M Mapping, 24, 38 Mass-spring-damper, 109, 121–123, 129 Maternal scaffolding, 46 Meaningful structure, 37 MEMS See Microelectronic mechanism systems (MEMS) Micro air vehicle, 145–156 Microelectronic mechanism systems (MEMS), Micro robots, 279, 283 Mirror neuron system (MNS), 49 MISO See Multi-input single-output (MISO) Mixed integer linear program, 31 MNS See Mirror neuron system (MNS) Mode, 162, 166, 167, 171, 172 Modeling linear, 117 nonlinear, 117, 118 Moment of inertia, 225, 228, 229 Motor experience, 41 Motor image, 38, 41 Move-phase, 239 313 Multi-input single-output (MISO), 229 Multipath, 75 Musculoskeletal system, 40 N Navigation module, Neonatal imitation, 41 Neural networks (NNs), 4, Nonholonomic constraints, 195 Nonholonomic WMRs, 196 Non-traversable area, 241 Normal stress, 214 O Object permanency, 38 Optical flow, 41 Optimal servo system, 252, 256–257 Organ identification, 41 P Passive dynamic walkers, 40 Path planning, 238 Persistent surveillance, 24 Physical embodiment, 37 PID, 118–120, 131 PID control, 15, 97, 102–107 Piezoelectric, 280, 281, 283, 284, 288 Pitch, 230, 235 Planetary exploration, 212 Point-to-multipoint communication, 137 Point weakness, 137 Polarization circular, 176–178, 183 elliptical, 178, 183 left handed, 183 left handed circular, 177, 183 linear, 176–178, 182, 183 right handed, 183 right handed circular, 177, 183 Potential energy, 129, 130 Pressure wave, 292, 293, 296, 298 Proprioceptive space, 42 Pursuit-evasion, 29 Push-pull, 225, 227–228 R Range sensor, 2, RCSS See Remote control support system (RCSS) 314 Reduces, 133 Remote control support system (RCSS), 86 Resilient control, Retarded functional differential equations (RFDEs), 27 Right-handed circular polarization (RHCP), 177, 178, 181, 183, 184, 190 Robust, 133 Roll, 230 Roll over, 40 Rotational angles, 228 Rotorcraft, 22 Rough terrain, 212 S Scaffolding, 38 Sea glider, 268, 269, 273, 275 Search, 23 Self Organizing Map (SOM), 48 Self/other discrimination/nondiscrimination, 49 Sensorimotor, 38 Sideslip angle, 13 Simultaneous localization and/or mapping (SLAM), 24, 31 Single wheel tester, 211 Six-legged robot, 251–262 SLAM See Simultaneous localization and/or mapping (SLAM) Sliding mode control (SMC), 120, 123, 124 Slip ratio, 212 Small electric helicopter, 73–83 SMC See Sliding mode control (SMC) Social interaction, 37 Sociality, 38 SOM See Self Organizing Map (SOM) Sonographic observations, 45 Spatial perception, 43 Spring-equivalent elastic model, 228, 229 State feedback controller, 135 Stride length, 246 Supercavitating flow, 291–298 Swing height, 244 Sympathy, 46 Synthetic aperture radar (SAR), 175, 176, 179 circularly polarized, 175, 176 CP-SAR, 175–190 linear polarized, 182, 184, 185 Synthetic approaches, 50 Syowa Station, 159, 168 Index T Takagaki–Sugeno–Kang (TSK), 223–235 Target detection, 29 Target tracking, 23, 24 Task assignment, 30, 34 Team coordination, 21 Technology readiness assessment (TRA), 55, 58 Technology readiness level (TRL), 55, 64 Terrain following and obstacle avoidance, 68 Thrust vectoring, 97, 98 Time-invariant system, 252, 258, 260 Time-varying system, 252, 257, 258, 260 Torque, 119 TRA See Technology readiness assessment (TRA) Tracking, 29 Tracking control, 196 TRL See Technology readiness level (TRL) TSK See Takagaki–Sugeno–Kang (TSK) U UAS autonomy technologies, 55 UAVs See Unmanned air vehicles (UAVs) UAV/UGV cooperation, 27 UAV/UGV teams, 34 UGVs See Unmanned ground vehicles (UGVs) Ultrasonic sensor, 74, 79–82 Ultrasound, 279, 281–283, 288 Unmanned aerial vehicle, 175–191 circularly polarized synthetic aperture radar (CP-SAR), 177, 178, 182, 183, 189–191 linear polarized, 185 linear polarized synthetic aperture radar (LP-SAR), 185 Unmanned aerial vehicles (UAVs) Josaphat Laboratory Experimental, 175, 177 Unmanned air vehicles (UAVs), 21, 159–173 Unmanned ground vehicles (UGVs), 21 V Vehicle autonomy, 33 Verbal communication, 38 Vertical takeoff and landing, 22 Virtual leader, 133 Visual tracking, 26 Vocalization, 38 Vortex, 113 Vortex flow, 299, 304, 305