Distributed Reactive Collision Avoidance - University of Washington

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University of Washington Graduate School This is to certify that I have examined this copy of a doctoral dissertation by Emmett Lalish and have found that it is complete and satisfactory in all respects, and that any and all revisions required by the final examining committee have been made. Chair of the Supervisory Committee: Kristi A. Morgansen Reading Committee: Kristi A. Morgansen Mehran Mesbahi Juris Vagners Date:
In presenting this dissertation in partial fulfillment of the requirements for the doctoral degree at the University of Washington, I agree that the Library shall make its copies freely available for inspection. I further agree that extensive copying of this dissertation is allowable only for scholarly purposes, consistent with “fair use” as prescribed in the U.S. Copyright Law. Requests for copying or reproduction of this dissertation may be referred to Proquest Information and Learning, 300 North Zeeb Road, Ann Arbor, MI 48106-1346, 1-800-521-0600, to whom the author has granted “the right to reproduce and sell (a) copies of the manuscript in microform and/or (b) printed copies of the manuscript made from microform.” Signature Date
Page 1: Distributed Reactive Collision Avoi
Page 5 and 6: TABLE OF CONTENTS Page List of Figu
Page 7 and 8: LIST OF FIGURES Figure Number Page
Page 9 and 10: ACKNOWLEDGMENTS The author wishes t
Page 11 and 12: 1 Chapter 1 INTRODUCTION TO COLLISI
Page 13 and 14: 3 system state as time goes to infi
Page 15 and 16: 5 imum speed. The constant-speed un
Page 17 and 18: 7 in [12], where the rates of chang
Page 19 and 20: 9 hybrid system that describes each
Page 21 and 22: 11 at first to be the holy grail of
Page 23 and 24: 13 Chapter 2 PROBLEM STATEMENT The
Page 25 and 26: 15 ⎡ ⎤ ⎡ ⎤ r sˆt d ⎢ s
Page 27 and 28: 17 Chapter 3 CONFLICTS AND COLLISIO
Page 29 and 30: 19 where t is the time to closest a
Page 31 and 32: 21 Enter Desired Control Deconflict
Page 33 and 34: 23 must know a bound on the maximum
Page 35 and 36: 25 Figure 4.2: Example optimization
Page 37 and 38: 27 cone is enlarged from (3.9) to (
Page 39 and 40: 29 Theorem 2. For vehicle i of an n
Page 41 and 42: 31 Figure 4.4: Example optimization
Page 43 and 44: 33 Theorem 3. For vehicle i of an n
Page 45 and 46: 35 fashion. The goal then is to hav
Page 47 and 48: 37 v ĩ v e p t,ijˆt i v j p n,ij
Page 49 and 50: 39 Figure 4.8: Example of the contr
Page 51 and 52: 41 Because of the symmetry of the p
Page 53 and 54:
43 also ensures that there is a nei
Page 55 and 56:
45 to adjust their trajectories to
Page 57 and 58:
47 controllers. The goal of these c
Page 59 and 60:
49 of a complex multiplicative unce
Page 61 and 62:
51 Proof. A multiplicative uncertai
Page 63 and 64:
53 u 1 u 2 θ γ v 2,max v 1,max Fi
Page 65 and 66:
55 speed (m/s) (a) 0.5 0.4 0.3 0.2
Page 67 and 68:
57 un (m/s 2 ) 0.2 0 (a) -0.2 0 5 1
Page 69 and 70:
59 10 8 ‖˜r‖ − dsep (m) 6 4
Page 71 and 72:
61 ‖˜r‖ − dsep (m) 4 2 0 (a)
Page 73 and 74:
63 Table 6.1: Comparison of computa
Page 75 and 76:
65 be stabilized with any of a vari
Page 77 and 78:
67 the heuristic performance will b
Page 79 and 80:
69 Chapter 7 CONCLUSION The primary
Page 81 and 82:
71 system of projecting everything
Page 83 and 84:
73 [11] G. Fasano, D. Accardo, and
Page 85 and 86:
75 [34] R. Skjetne, S. Moi, and T.
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Distributed Reactive Collision Avoidance - University of Washington

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