New Development on Sense and Avoid Strategies for Unmanned Aerial Vehicles

101 Pages·2016·3.89 MB·English

New Development on Sense and Avoid Strategies
for Unmanned Aerial Vehicles
YuFu
AThesis
in
TheDepartment
of
MechanicalandIndustrialEngineering
PresentedinPartialFulfillmentoftheRequirements
fortheDegreeof
MasterofAppliedScience(MechanicalEngineering)at
ConcordiaUniversity
Montre´al,Que´bec,Canada
February2016
©YuFu,2016
CONCORDIA UNIVERSITY
School of Graduate Studies
Thisistocertifythatthethesisprepared
By: YuFu
Entitled: New Development on Sense and Avoid Strategies for Unmanned
AerialVehicles
andsubmittedinpartialfulfillmentoftherequirementsforthedegreeof
MasterofAppliedScience(MechanicalEngineering)
complies with the regulations of this University and meets the accepted standards with
respecttooriginalityandquality.
SignedbytheFinalExaminingCommittee:
Chair
Dr. Chun-YiSu
ExternalExaminer
Dr. ZhenhuaZhu
Examiner
Dr. SubhashRakheja
Supervisor
Dr. YouminZhang
Approvedby
MartinD.Pugh,Chair
DepartmentofMechanicalandIndustrialEngineering
2016
AmirAsif,Dean
FacultyofEngineeringandComputerScience
Abstract
New Development on Sense and Avoid Strategies for Unmanned Aerial
Vehicles
YuFu
Unmanned Aerial Vehicles (UAVs) can carry out more complex civilian and military
applications with less cost and more flexibility in comparison of manned aircraft. Mid-air
collision thus becomes profoundly important considering the safe operation of air trans-
portation systems, when UAVs are increasingly used more with various applications and
share the same airspace with manned air vehicles. To ensure safe flights, UAVs have to
configureSenseandAvoid(S&A)systemsperformingnecessarymaneuverstoavoidcolli-
sions. AfteranalyzingthemannerofS&Asystem,avoidancestrategiesbasedonasubsetof
possible collision scenarios are proposed in this thesis. 1) To avoid a face-to-face intruder,
a feasible trajectory is generated by differential geometric guidance, where the constraints
of UAV dynamics are considered. 2) The Biogeography Based Optimization (BBO) ap-
proach is exploited to generate an optimal trajectory to avoid multiple intruders’ threats
in the landing phase. 3) By formulating the collision avoidance problem within a Markov
Decision Process (MDP) framework, a desired trajectory is produced to avoid multiple in-
truders in the 2D plane. 4) MDP optimization method is extended to address the problem
ofoptimal3Dconflictresolutioninvolvingmultipleaircraft. 5)Consideringthatthesafety
of UAVsis directlyrelated tothe dynamicconstraints, thedifferential flatnesstechnique is
developed to smoothen the optimal trajectory. 6) Energy based controller is designed such
thattheUAViscapableoffollowingthegeneratedtrajectory.
iii
Acknowledgments
Firstly, I would like to express my sincere gratitude to my supervisor, Dr. Youmin
Zhang, for professional supervision and his scientific assistance, constant help, advice,
guidanceandgoodmoodthroughouttheyears.
I would like to express my sincere thanks to Dr. Xiang Yu, for his enthusiasm for
research and challenging projects. His continuous support and very helpful inputs eased
the hardship that faced me throughout flight simulation and paper writing. I am grateful
thatIhadtheopportunitytoworkwithandlearnsomuchfromhim.
I would also like to acknowledge and thank Puthy Soupin, Phil Cole at the Marinvent
Corporation, who were helpful in giving their experience and advice that were useful in
achievingcooperatedproject. Ialsowishtothankallmembersoflabforgenerouslysharing
theiryearsofexperience.
Last but not least, I would like to thank my loving and caring family. My deepest
gratitude goes to my beloved parents for their endless love, prayers and encouragement. It
would not have been possible for me to reach where I am without their support, patience
and care. I would also like to express my appreciation to my sister and friends who were
alwayssupportingandencouragingmewiththeirbestwishes.
iv
Contents
ListofFigures viii
ListofTables x
1 Introduction 1
1.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 Challenges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.3 Contributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.4 OrganizationoftheThesis . . . . . . . . . . . . . . . . . . . . . . . . . . 4
2 LiteratureReview 5
2.1 SurveyonSensors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
2.1.1 CooperativeSensors . . . . . . . . . . . . . . . . . . . . . . . . . 5
2.1.2 Non-CooperativeSensors . . . . . . . . . . . . . . . . . . . . . . 6
2.1.3 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
2.2 SurveyonCollisionDetectionApproaches . . . . . . . . . . . . . . . . . . 8
2.3 SurveyonCollisionAvoidanceApproaches . . . . . . . . . . . . . . . . . 10
2.3.1 Sampling-BasedCollisionAvoidanceApproaches . . . . . . . . . 11
2.3.2 DecoupledCollisionAvoidanceApproaches . . . . . . . . . . . . 13
2.3.3 NumericalOptimizationApproaches . . . . . . . . . . . . . . . . 14
2.3.4 ArtificialHeuristicApproaches . . . . . . . . . . . . . . . . . . . 16
2.3.5 OtherMethods . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
2.3.6 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
3 ProblemFormulation 20
3.1 UAVDynamics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
3.2 Formulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
3.3 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
v
4 SenseandCollisionAvoidanceofUnmannedAerialVehiclesUsingDifferential
GeometricGuidanceandFlatnessApproach 29
4.1 DifferentialGeometricGuidance(DGG)BasedCollisionResolution . . . . 29
4.2 PathPlanning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
4.2.1 DifferentialFlatnessBasedApproach . . . . . . . . . . . . . . . . 31
4.2.2 TrajectoryPlanningunderUAVConstraints . . . . . . . . . . . . . 32
4.3 ExperimentalResults . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
4.3.1 ExperimentalPlatform . . . . . . . . . . . . . . . . . . . . . . . . 33
4.3.2 TestingScenarios . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
4.3.3 ExperimentalResultsandEvaluations . . . . . . . . . . . . . . . . 35
4.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
5 SenseandCollisionAvoidanceofUnmannedAerialVehiclesUsingBiogeogra-
phyBasedOptimizationApproach 40
5.1 CollisionAvoidanceAlgorithm . . . . . . . . . . . . . . . . . . . . . . . . 40
5.1.1 Biogeography-BasedOptimization(BBO) . . . . . . . . . . . . . . 41
5.1.2 TheIntegrationofUAVDynamicsinthePlannedPath . . . . . . . 45
5.1.3 Implementaion of the Proposed BBO with Differential Flatness to
AvoidCollisions . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
5.2 PathFollowingControllerDesign . . . . . . . . . . . . . . . . . . . . . . 50
5.2.1 ControllerDesign . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
5.3 SimulationandResultsAnalysis . . . . . . . . . . . . . . . . . . . . . . . 53
5.3.1 SimulationScenarios . . . . . . . . . . . . . . . . . . . . . . . . . 53
5.3.2 PerformanceAnalysis . . . . . . . . . . . . . . . . . . . . . . . . 55
5.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
6 Sense and Collision Avoidance of Unmanned Aerial Vehicles Using Markov
DecisionProcessandFlatnessApproach 62
6.1 MDPBasedCollisionAvoidancein2DPlane . . . . . . . . . . . . . . . . 63
6.1.1 MarkovDecisionProcess . . . . . . . . . . . . . . . . . . . . . . 63
6.1.2 PolicyIteration . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66
6.1.3 TheIntegrationofUAVDynamicsinthePlannedPath . . . . . . . 67
6.1.4 Validation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
6.1.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
6.2 MDPBasedCollisionAvoidancein3DPlane . . . . . . . . . . . . . . . . 71
6.2.1 PathPlanningin3D . . . . . . . . . . . . . . . . . . . . . . . . . 71
vi
6.2.2 PathFollowingControllerDesign . . . . . . . . . . . . . . . . . . 74
6.2.3 SimulationStudies . . . . . . . . . . . . . . . . . . . . . . . . . . 76
6.2.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81
7 ConclusionsandFutureWork 83
7.1 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83
7.2 FutureWork . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83
7.3 MyPublicationsRelatedtotheThesis . . . . . . . . . . . . . . . . . . . . 84
Bibliography 85
vii
List of Figures
Figure1.1 TheillustrativeschemeofS&AfunctionalityinaUAV. . . . . . . . 2
Figure2.1 Illustrationoftypicalsensingdevices. . . . . . . . . . . . . . . . . 8
Figure2.2 Collisiondetectionmethod. . . . . . . . . . . . . . . . . . . . . . . 9
Figure2.3 CategoriesofUAVcollisionavoidanceapproaches. . . . . . . . . . 11
Figure3.1 AmodelofforcesinUAVinertialframe. . . . . . . . . . . . . . . 24
Figure3.2 TherelativemotionofaUAVandanIntruder. . . . . . . . . . . . . 25
Figure3.3 Grid-basedtrajectoryrepresentation. . . . . . . . . . . . . . . . . . 28
Figure4.1 Geometryofcollisionresolution. . . . . . . . . . . . . . . . . . . . 30
Figure4.2 TheplatformforvalidatingS&Ascheme. . . . . . . . . . . . . . . 34
Figure4.3 OriginaltrajectorieswithoutS&A. . . . . . . . . . . . . . . . . . . 35
Figure4.4 ResultsinScenario1. . . . . . . . . . . . . . . . . . . . . . . . . . 36
Figure4.5 ResultsofScenario2. . . . . . . . . . . . . . . . . . . . . . . . . . 37
Figure4.6 ResultsofScenario3. . . . . . . . . . . . . . . . . . . . . . . . . . 38
Figure4.7 ResultsofScenario4. . . . . . . . . . . . . . . . . . . . . . . . . . 39
Figure5.1 Simplifiedmigrationmodelofhabitat. . . . . . . . . . . . . . . . . 42
Figure5.2 HabitatmodificationofBBO. . . . . . . . . . . . . . . . . . . . . . 43
Figure5.3 HabitatmutationofBBO. . . . . . . . . . . . . . . . . . . . . . . . 45
Figure5.4 Theprocedureoftheproposedapproach. . . . . . . . . . . . . . . . 49
Figure5.5 Thestructureoftheenergy-basedcontroller. . . . . . . . . . . . . . 51
Figure5.6 TheUAV-intruderscollisionavoidancescenario. . . . . . . . . . . . 55
Figure5.7 ActualtrajectoryofUAVincollisionavoidancescenario. . . . . . . 56
Figure5.8 UAVoutputresponsesinfollowingreferencepitchanglescenario. . 57
Figure 5.9 Elevator angle and throttle angle responses in following reference
pitchanglescenario. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58
Figure5.10 UAVoutputresponsesinfollowingreferencealtitudescenario. . . . 58
Figure 5.11 Elevator angle and throttle angle responses in following reference
altitudescenario. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
viii
Figure5.12 PitchangleofUAVincollisionavoidancescenario. . . . . . . . . . 59
Figure5.13 Actualaltitudeandvelocityincollisionavoidancescenario. . . . . . 60
Figure 5.14 Actual elevator angle and throttle angle in collision avoidance sce-
nario. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60
Figure6.1 ThebasicactionofUAV. . . . . . . . . . . . . . . . . . . . . . . . 64
Figure6.2 Theassignmentofthetransitionprobability. . . . . . . . . . . . . . 65
Figure6.3 TheUAV-intruderscollisionavoidancescenario. . . . . . . . . . . 68
Figure6.4 TrajectoryoftheUAV. . . . . . . . . . . . . . . . . . . . . . . . . . 69
Figure6.5 xpositionerror. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70
Figure6.6 y positionerror. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70
Figure6.7 Theaccumulativeerrorsinxandy positions. . . . . . . . . . . . . . 71
Figure6.8 ThebasicactionofUAVin3Dplane. . . . . . . . . . . . . . . . . . 73
Figure6.9 Theassignmentofthetransitionprobabilityin3Dplane. . . . . . . 74
Figure6.10 Thepathfollowingcontroller. . . . . . . . . . . . . . . . . . . . . . 75
Figure6.11 Thereferencesignalduringthelandingstage. . . . . . . . . . . . . 78
Figure6.12 The3DtrajectoryoftheUAVlanding. . . . . . . . . . . . . . . . . 80
Figure6.13 TheUAVpositioninformationwithrespecttothreedirections. . . . 80
Figure6.14 ThetrackingperformanceofEulerangles. . . . . . . . . . . . . . . 80
Figure6.15 TheresponsesoftheUAVactuators. . . . . . . . . . . . . . . . . . 81
Figure6.16 Thetrackingerrors. . . . . . . . . . . . . . . . . . . . . . . . . . . 81
ix
List of Tables
Table2.1 Thecharacteristicsofsensortechnologies . . . . . . . . . . . . . . . 8
Table4.1 Minimumrelativedistance . . . . . . . . . . . . . . . . . . . . . . . 36
Table5.1 Referencepitchangledescribtion . . . . . . . . . . . . . . . . . . . 54
Table5.2 Referencealtitudedescribtion . . . . . . . . . . . . . . . . . . . . . 54
Table5.3 Theinitialparametersforsimulation . . . . . . . . . . . . . . . . . . 54
Table6.1 TheoperatingoftheUAV . . . . . . . . . . . . . . . . . . . . . . . 76
Table6.2 ThedesignparametersoftheUAV . . . . . . . . . . . . . . . . . . . 77
x