Navigation Functionalities for an Autonomous UAV Helicopter

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Bibliography BIBLIOGRAPHY [1] MARVIN: TU Berlin. http://pdv.cs.tu-berlin.de/MARVIN/. [2] P. Doherty. Advanced Research with Autonomous Unmanned Aerial Vehicles. In Proc. of the Int. Conf. on the Principles of Knowledge Representation and Reasoning, pages 731–732, 2004. [3] P. Doherty, P. Haslum, F. Heintz, T. Merz, T. Persson, and B. Wingman. A Distributed Architecture for Autonomous Unmanned Aerial Vehicle Experimentation. In Proc. of the Int. Symp. on Distributed Autonomous Robotic Systems, pages 221–230, 2004. [4] S. Duranti and G. Conte. In-flight identification of the augmented flight dynamics of the rmax unmanned helicopter. In Proc. of the 17th IFAC Symp. on Automatic Control in Aerospace, 2007. [5] M. Egerstedt, X. Hu, and A. Stotsky. Control of mobile platforms using a virtual vehicle approach. IEEE Transactions on Automatic Control, 46(11):1777–1782, November 2001. [6] M. Egerstedt, T. J. Koo, F. Hoffmann, and S. Sastry. Path planning and flight controller scheduling for an autonomous helicopter. Lecture Notes in Computer Science, 1569:91–102, 1999. [7] Bernard Etkin and Lloid Duff Reid. Dynamic of Flight: Stability and Control. John Wiley and Sons, Inc., 1995. [8] J.A. Farrell and M. Barth. The Global Positioning System and Inertial Navigation. McGraw-Hill, 1998.
BIBLIOGRAPHY 73 [9] E. Frazzoli. Robust Hybrid Control for Autonomous Vehicle Motion Planning. PhD thesis, Massachusetts Institute of Technology, 2001. [10] MIT/Draper Autonomous Helicopter Project. http://web.mit.edu/whall/www/heli/. [11] Object Computing Inc. Tao developers guide, version 1.1a. 2000. [12] R.E. Kalman. A new approach to linear filtering and prediction problems. Transactions of the ASME-Journal of Basic Engineering, 82 (Series D): 35-45, 1960. [13] Jay Hyoun Kwon. Airborne Vector Gravimetry Using GPS/INS. Master Thesis, The Ohio State University, 2000. [14] P Mantegazza et. al. RTAI: Real time application interface. Linux Journal, 72, April 2000. [15] T. Merz. Building a System for Autonomous Aerial Robotics Research. In Proc. of the IFAC Symp. on Intelligent Autonomous Vehicles, 2004. [16] B. Mettler, M.B. Tischler, and T. Kanade. System identification of small-size unmanned helicopter dynamics. American Helicopter Society 55th Annual Forum Proceedings, May 1999. [17] Doherty P., Granlund G., Kuchcinski K., Sandewall E., Nordberg K., Skarman E., and Wiklund J. The WITAS unmanned aerial vehicle project. In Proc. of the European Conf. on Artificial Intelligence, pages 747–755, 2000. [18] P-O Pettersson. Using Randomized Algorithms for Helicopter Path Planning. Linköping, Sweden, 2006. Lic. Thesis Linköping University. [19] AVATAR: USC Autonomous Flying Vehicle Project. http://wwwrobotics.usc.edu/∼avatar. [20] Raymond W. Prouty. Helicopter Performance, Stability and Control. Krieger Publishing Company, 1995.
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Linköping Studies in Science and T
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Acknowledgements This work would ha
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Contents 1 Introduction 1 2 Overvie
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Chapter 1 Introduction An Unmanned
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of the environment in order to avoi
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Chapter 2 Overview This chapter pre
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2.1. UAV SOFTWARE ARCHITECTURE 7 wh
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2.2. THE UAV HELICOPTER PLATFORM 9
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2.2. THE UAV HELICOPTER PLATFORM 11
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Chapter 3 Simulation 3.1 Introducti
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3.2. HARDWARE-IN-THE-LOOP SIMULATIO
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3.3. REFERENCE FRAMES 17 3.3 Refere
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3.4. THE AUGMENTED RMAX DYNAMIC MOD
Page 31 and 32: 3.4. THE AUGMENTED RMAX DYNAMIC MOD
Page 33 and 34: 3.5. SIMULATION RESULTS 23 3.5 Simu
Page 35 and 36: 3.5. SIMULATION RESULTS 25 Figure 3
Page 37 and 38: 3.5. SIMULATION RESULTS 27 Figure 3
Page 39 and 40: Chapter 4 Path Following Control Mo
Page 41 and 42: 4.2. TRAJECTORY GENERATOR 31 Figure
Page 43 and 44: 4.2. TRAJECTORY GENERATOR 33 Fig. 4
Page 45 and 46: 4.2. TRAJECTORY GENERATOR 35 be use
Page 47 and 48: 4.2. TRAJECTORY GENERATOR 37 4.2.3
Page 49 and 50: 4.2. TRAJECTORY GENERATOR 39 radius
Page 51 and 52: 4.2. TRAJECTORY GENERATOR 41 Calcul
Page 55 and 56: 4.2. TRAJECTORY GENERATOR 45 by the
Page 59 and 60: 4.3. OUTER LOOP CONTROL EQUATIONS 4
Page 61 and 62: 4.4. EXPERIMENTAL RESULTS 51 Up [m]
Page 63 and 64: 4.5. CONCLUSIONS 53 1 + s 1 C(s) =
Page 65 and 66: 4.5. CONCLUSIONS 55 Vel [m/s] 20 18
Page 67 and 68: Chapter 5 Sensor fusion for vision
Page 69 and 70: composed of three accelerometers an
Page 71 and 72: 5.1. FILTER ARCHITECTURE 61 filter
Page 73 and 74: 5.1. FILTER ARCHITECTURE 63 north,
Page 75 and 76: 5.2. EXPERIMENTAL RESULTS 65 Figure
Page 77 and 78: 5.2. EXPERIMENTAL RESULTS 67 Figure
Page 79 and 80: 5.2. EXPERIMENTAL RESULTS 69 by the
Page 81: 5.3. CONCLUSION 71 vision system st
Page 85 and 86: Appendix A 75
Page 87 and 88: A.1. PAPER I 77 is a three-dimensio
Page 89 and 90: A.1. PAPER I 79 The reference point
Page 91 and 92: A.1. PAPER I 81 Path Av Err Max Err
Page 93 and 94: A.2. PAPER II 83 From Motion Planni
Page 107 and 108: A.3. PAPER III 97 A.3 Paper III Aut
Page 109 and 110: A.3. PAPER III 99 the projection of
Page 111 and 112: A.3. PAPER III 101 yes Tbo > Tlim2
Page 113 and 114: A.3. PAPER III 103 immediately afte
Page 115 and 116: A.3. PAPER III 105 altitude [m] 20
Page 117: A.3. PAPER III 107 Fig. 10. Flight
Page 121 and 122: Department of Computer and Informat
Page 123 and 124: No 598 Rego Granlund: C 3 Fire - A
Page 125 and 126: No 1024 Aleksandra Tešanovic: Towa
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