flying animal inspired behavior-based gap-aiming autonomous flight with a small unmanned ...

128 Pages·2017·5.04 MB·English

FLYINGANIMALINSPIREDBEHAVIOR-BASEDGAP-AIMINGAUTONOMOUS
FLIGHTWITHASMALLUNMANNEDROTORCRAFTINARESTRICTED
MANEUVERABILITYENVIRONMENT
ADissertation
by
TRACIANNSARMIENTO
SubmittedtotheOfficeofGraduateandProfessionalStudiesof
TexasA&MUniversity
inpartialfulfillmentoftherequirementsforthedegreeof
DOCTOROFPHILOSOPHY
ChairofCommittee, RobinMurphy
CommitteeMembers, YoonsuckChoe
DylanShell
MichaelSmotherman
HeadofDepartment, DilmaDaSilva
August 2017
Major Subject: Computer Science
Copyright2017 TraciAnnSarmiento
ABSTRACT
Thisdissertationresearchshowsasmallunmannedrotorcraftsystemwithonboardpro-
cessing and a vision sensor can produce autonomous, collision-free flight in a restricted
maneuverability environment with no a priori knowledge by using a gap-aiming behavior
inspiredbyflyinganimals. Currentapproachestoautonomousflightwithsmallunmanned
aerialsystems(SUAS)concentrateondetectingandexplicitlyavoidingobstacles. Incon-
trast, biology indicates that birds, bats, and insects do the opposite; they react to open
spaces, or gaps in the environment, with a gap_aiming behavior. Using flying animals
as inspiration a behavior-based robotics approach is taken to implement and test their ob-
served gap-aiming behavior in three dimensions. Because biological studies were unclear
whether the flying animals were reacting to the largest gap perceived, the closest gap
perceived, or all of the gaps three approaches for the perceptual schema were explored
in simulation: detect_closest_gap, detect_largest_gap, and detect_all_gaps. The result
of these simulations was used in a proof-of-concept implementation on a 3DRobotics
Solo quadrotor platform in an environment designed to represent the navigational diffi-
culties found inside a restricted maneuverability environment. The motor schema is im-
plemented with an artificial potential field to produce the action of aiming to the center of
the gap. Through two sets of field trials totaling fifteen flights conducted with a small
unmanned quadrotor, the gap-aiming behavior observed in flying animals is shown to
produce repeatable autonomous, collision-free flight in a restricted maneuverability en-
vironment. Additionally, using the distance from the starting location to perceived gaps,
the horizontal and vertical distance traveled, and the distance from the center of the gap
ii
during traversal the implementation of the gap selection approach performs as intended,
the three-dimensional movement produced by the motor schema and the accuracy of the
motor schema are shown, respectively. This gap-aiming behavior provides the robotics
community with the first known implementation of autonomous, collision-free flight on a
small unmanned quadrotor without explicit obstacle detection and avoidance as seen with
current implementations. Additionally, the testing environment described by quantitative
metrics provides a benchmark for autonomous SUAS flight testing in confined environ-
ments. Finally, the success of the autonomous collision-free flight implementation on a
small unmanned rotorcraft and field tested in a restricted maneuverability environment
couldhaveimportantsocietalimpactinboththepublicandprivatesectors.
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DEDICATION
ToAndre,butforMichelleandherboys
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ACKNOWLEDGMENTS
My time at Texas A&M University may have been short, but the list of mentors, col-
leagues,friends,andfamilyIneedtothankislong.
First, I would like to express my most sincere gratitude to my advisor, Dr. Robin
Murphy. Your dedication, focus, and resiliency is to be admired. You pushed me to think
bigger,workharder,digdeeper,andwritebetteroverthesepastthreeyears. Thankyoufor
takingonthis“specialcase”. Totherestofmycommitteemembers: thankyou. Dr. Dylan
Shell,youhaveauniqueabilitytoprovidefeedbackinawaythatisbothconstructiveand
motivating. The time you took to dispense your point of view improved the outcome of
this research. Dr. Michael Smotherman, I appreciate the insights you gave to refine my
take on the ethological studies. Of course, touring your lab was one of the highlights of
my time here. I can’t decide whether working with bats, or robots is more amazing! Dr.
Choe,thankyoufortakingthetimetoparticipateonmycommittee.
Thenumberofpeoplethatfallintothecolleaguesandfriendscategoriesaretoonumer-
ous to include here, but if you’re reading this and consider yourself part of those groups
pleaseacceptmyheartfeltthankyou.
And now, we come to family. Simply put, I am blessed. Even if I was given the
opportunity to choose all those years ago, I could not have selected two better folks to be
myparent. Lind-erandDave,whoarebetterknownasGrandmaandGrandpathesedays,
have been my biggest fans since day one. If I had to name the one thing that made all the
difference, it was your expectations. Thank you for setting the bar high and providing me
withtheskills,opportunities,andloveneededtovaultoverit.
Team Sarmiento: WE DID IT!!!! Eva, those exclamations are for you. ;) Lincoln,
in our time here I’ve watched you turn from our toddler ”Lincoln-big-boy-bigger” into
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the amazing kindergarten graduate who wants to change his name to ”Abe”, so he can
become President of the United States one day. I have no doubt you’ll achieve that dream
if you channel all that energy (especially your 0500 energy), and never lose the infectious
giggle or the sparkle that lights up your eyes when you smile. Eva, my sweet baby Goo,
you’ve turned into a young lady right before our eyes. You’re quiet and introspective, but
independent and fiercely loyal. With your heart and smarts, look out world! You told me
last year you were going to visit Saturn to slide around its rings and I can’t wait to wave
to you as you launch into history. Finally, Andre. There’s nothing to say except I could
not have done this without you. Oh, but who are we kidding....I always have more to say.
You have let me chase my dream over these last 10 years of marriage. We’re looking at
move number 5 through 3 states and 2 countries. We’ve added 2 kiddos, 2 dogs, and 3
cats to Team Sarmiento over the years, and said goodbye to irreplaceable members of our
family. You’vebeenmypartnerthroughitallandquietlytakencareofourhome,ourkids,
our pets, our parents, and me without complaint by reinventing yourself countless times.
Here’stomanymoredecadesofadventures!
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CONTRIBUTORSANDFUNDINGSOURCES
Contributors
This work was supported by a dissertation committee consisting of Professor Robin
Murphy [advisor], Professor Yoonsuck Choe, and Professor Dylan Shell of the Depart-
ment of Computer Science and Engineering and Professor Michael Smotherman of the
DepartmentofBiology.
Allworkconductedforthedissertationwascompletedbythestudentindependently.
FundingSources
Graduate study was supported by the Department of Computer Science and Engineer-
ingatTexasA&MUniversity.
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NOMENCLATURE
SUAS SmallUnmannedAerialSystem
MAV MicroAerialVehicle
FOV FieldofView
APF ArtificialPotentialField
IBVS Image-basedVisualServoControl
PBVS Pose-basedVisualServoControl
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TABLEOFCONTENTS
Page
ABSTRACT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ii
DEDICATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iv
ACKNOWLEDGMENTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v
CONTRIBUTORSANDFUNDINGSOURCES . . . . . . . . . . . . . . . . . . vii
NOMENCLATURE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . viii
TABLEOFCONTENTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ix
LISTOFFIGURES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xiii
LISTOFTABLES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xv
1. INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.1 ResearchQuestion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.2 FlyingAnimalBehavior-basedAutonomousSUAS . . . . . . . . . . . . 3
1.3 ContributionsoftheResearch . . . . . . . . . . . . . . . . . . . . . . . . 4
1.4 OrganizationoftheDissertation . . . . . . . . . . . . . . . . . . . . . . 6
2. RELATEDWORK . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
2.1 ReactiveControlofObstacleAvoidanceforSUAS . . . . . . . . . . . . . 8
2.1.1 Sensors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
2.1.2 PerceptualSchemasandPercepts . . . . . . . . . . . . . . . . . . 9
2.1.3 MotorSchemas . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
2.2 LimitationsofCurrentImplementations . . . . . . . . . . . . . . . . . . 12
2.2.1 OperationinTwoDimensions . . . . . . . . . . . . . . . . . . . 12
2.2.2 MotorActionsUselessinRestrictedManeuverabilityEnvironments 14
2.3 Reaction: ObstaclesversusGaps . . . . . . . . . . . . . . . . . . . . . . 14
2.4 ExperimentalEnvironmentsandMetrics . . . . . . . . . . . . . . . . . . 14
2.5 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
2.6 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
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3. BACKGROUND:FLYINGANIMALS . . . . . . . . . . . . . . . . . . . . . 18
3.1 IntroductiontoEthologicalLiteratureReview . . . . . . . . . . . . . . . 18
3.2 SensorsUsedforDetection . . . . . . . . . . . . . . . . . . . . . . . . . 21
3.2.1 PassiveSensingThroughVision . . . . . . . . . . . . . . . . . . 23
3.2.2 ActiveSensingThroughSonar . . . . . . . . . . . . . . . . . . . 24
3.3 PerceptualSchemas: Environment . . . . . . . . . . . . . . . . . . . . . 24
3.3.1 PerceptualSchema: detect_object . . . . . . . . . . . . . . . . . 25
3.3.1.1 DetectingMovingandStationaryObjects . . . . . . . . 25
3.3.1.2 DistancetoanObject . . . . . . . . . . . . . . . . . . 28
3.3.1.3 DeterminingGapSize . . . . . . . . . . . . . . . . . . 28
3.3.1.4 DeterminingObjectSize . . . . . . . . . . . . . . . . . 29
3.3.1.5 DeterminingPercentofViewSubtended . . . . . . . . 29
3.3.2 PerceptualSchema: Others . . . . . . . . . . . . . . . . . . . . . 29
3.3.2.1 DetectingAltitude . . . . . . . . . . . . . . . . . . . . 29
3.3.2.2 DeterminingDistanceFlown . . . . . . . . . . . . . . . 29
3.3.2.3 DetectingPredators . . . . . . . . . . . . . . . . . . . 30
3.3.2.4 DetectingPrey . . . . . . . . . . . . . . . . . . . . . . 30
3.3.2.5 DetectingaMate . . . . . . . . . . . . . . . . . . . . . 30
3.3.2.6 DetectingWalls . . . . . . . . . . . . . . . . . . . . . 30
3.4 PerceptualSchemas: AdaptiveSensing . . . . . . . . . . . . . . . . . . . 31
3.4.1 DistancetoanObject . . . . . . . . . . . . . . . . . . . . . . . . 31
3.4.2 DetectingMovingandStationaryObjects . . . . . . . . . . . . . 32
3.4.3 DeterminingGapSizeandAltitude . . . . . . . . . . . . . . . . 32
3.5 MotorSchemas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
3.5.1 AvoidObjects . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
3.5.1.1 MotorSchema: aim_gap_center . . . . . . . . . . . . . 33
3.5.1.2 MotorSchema: turn_brakeorturn_speed . . . . . . . . 35
3.5.1.3 MotorSchema: maintain_angular_velocity . . . . . . . 35
3.5.1.4 MotorSchema: stabilize_gaze . . . . . . . . . . . . . . 35
3.5.1.5 MotorSchema: adjust_pulse . . . . . . . . . . . . . . . 36
3.5.1.6 MotorSchema: adjust_beam_aim . . . . . . . . . . . . 36
3.5.1.7 MotorSchema: modify_saccades . . . . . . . . . . . . 37
3.5.1.8 MotorSchema: change_sensor . . . . . . . . . . . . . 37
3.5.1.9 MotorSchema: return_to_food . . . . . . . . . . . . . 37
3.5.1.10 MotorSchema: maintain_CATD . . . . . . . . . . . . . 37
3.5.1.11 MotorSchema: appear_stationary . . . . . . . . . . . . 38
3.5.1.12 MotorSchema: balance_lateral_motion . . . . . . . . . 38
3.6 Observations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
3.7 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
4. APPROACH . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42
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