Trends in Control and Decision-Making for Human–Robot Collaboration Systems

424 Pages·2017·15.032 MB·English

by  Yue Wang, Fumin Zhang (eds.)

Yue Wang · Fumin Zhang Editors
Trends in Control and
Decision-Making
for Human–Robot
Collaboration Systems
Trends in Control and Decision-Making
–
for Human Robot Collaboration Systems
Yue Wang Fumin Zhang
(cid:129)
Editors
Trends in Control
and Decision-Making
–
for Human Robot
Collaboration Systems
123
Editors
Yue Wang Fumin Zhang
Department ofMechanical Engineering Schoolof Electrical andComputer
Clemson University Engineering
Clemson, SC Georgia Institute of Technology
USA Atlanta, GA
USA
ISBN978-3-319-40532-2 ISBN978-3-319-40533-9 (eBook)
DOI 10.1007/978-3-319-40533-9
LibraryofCongressControlNumber:2016959746
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To our advisors, students, and family
Preface
Thisbookaimstopresentnewdevelopmentsincontrolanddecision-makingtheory
in the field of human–robot interaction (HRI). Despite advances in robotics,
sensing, and autonomy, human participation is still an essential component in
various operations, especially under uncertain and complex environments. In par-
ticular,human–robotcollaboration(HRC)systemsintegratethestrengthsofhuman
intermsofhigh-leveldecision-making,flexibility,dexterity,visionprocessing,etc.,
with robot’s capabilities of performing repetitive tasks in dangerous situations in
ordertorealizethefullpotentialofautonomoussystems.Therefore,aconsiderable
amount of effort has been made in this area, which however still lacks qualitative
analysis, performance prediction, and guarantees. This offers little insight into the
effectivecontrolanddecision-makingforthecollaborationoperations,especiallyin
real time.
Tofillthegap,thechaptersinthisbookdiscussindetailthedevelopmentofnew
control and decision-making algorithms for HRC systems for guaranteed joint
human–robot system performance. Chapter 1 provides an overview of the extant
works in HRI and detailed introduction of main contributions of each chapter.
Chapters 2–9 present methods for one human–robot pair collaboration and
Chaps. 10–16 develop the control and coordination algorithms for humans to
collaboratewithmultiplerobotsandswarms.Bothphysical(e.g.,force,vision)and
psychological human factors (e.g., trust and regret) are embedded into control and
decision-making approaches such as nonlinear control, shared control, switching
control, optimal control, and sequential detection. The considered applications
include transportation, healthcare, manufacturing, and defense. Robot experiments
and simulations with human-in-the-loop are conducted to demonstrate the effec-
tiveness of the proposed algorithms.
Clemson, SC, USA Yue Wang
Atlanta, GA, USA Fumin Zhang
April 2016
vii
Acknowledgements
The editors would like to thank all the chapter authors and reviewers that work
together on this book. A special acknowledgment goes to all the graduate students
intheInterdisciplinaryandIntelligentResearch(I2R)LaboratoryintheMechanical
Engineering Department at Clemson University, whom assisted the editors to
reviewchaptersand provideduseful feedbacksto improve thequality ofthe book.
The first editor would like to thank the support from the National Science
FoundationunderGrantNo.CMMI-1454139.Theeditorswouldalsoliketothank
Springer Verlag and its stafffor the professional support.
ix
Contents
1 Introduction .... .... .... ..... .... .... .... .... .... ..... .. 1
Yue Wang and Fumin Zhang
1.1 Overview.. .... .... ..... .... .... .... .... .... ..... .. 1
1.2 Collaboration Between One Human–Robot Pair . .... ..... .. 4
1.3 Collaboration Between Human and Multiple
Robots/Swarms . .... ..... .... .... .... .... .... ..... .. 6
References .. .... .... .... ..... .... .... .... .... .... ..... .. 8
2 Robust Shared-Control for Rear-Wheel Drive Cars . .... ..... .. 15
Jingjing Jiang and Alessandro Astolfi
2.1 Introduction.... .... ..... .... .... .... .... .... ..... .. 15
2.2 Problem Formulation, Definitions, and Assumptions .. ..... .. 16
2.3 Design of the Shared-Control Law with Measurements
of Absolute Positions. ..... .... .... .... .... .... ..... .. 19
2.3.1 Design of the Feedback Controller. .... .... ..... .. 19
2.3.2 Shared-Control Algorithm.... .... .... .... ..... .. 22
2.4 Disturbance Rejections..... .... .... .... .... .... ..... .. 25
2.5 Design of the Shared Control Without Measurements
of Absolute Positions. ..... .... .... .... .... .... ..... .. 28
2.5.1 Design of the Feedback Controller. .... .... ..... .. 29
2.5.2 Shared-Control Algorithm.... .... .... .... ..... .. 31
2.6 Case Studies ... .... ..... .... .... .... .... .... ..... .. 33
2.6.1 Case I: Turning Without Absolute Positioning..... .. 33
2.6.2 Case II: Driving on a Road with Parked Cars. ..... .. 36
2.6.3 Case III: Emergency Breaking .... .... .... ..... .. 36
2.7 Conclusions.... .... ..... .... .... .... .... .... ..... .. 38
References .. .... .... .... ..... .... .... .... .... .... ..... .. 38
xi
xii Contents
3 Baxter-On-Wheels (BOW): An Assistive Mobile Manipulator
for Mobility Impaired Individuals.... .... .... .... .... ..... .. 41
Lu Lu and John T. Wen
3.1 Introduction.... .... ..... .... .... .... .... .... ..... .. 41
3.2 System Description .. ..... .... .... .... .... .... ..... .. 44
3.2.1 Experimental Platform: BOW. .... .... .... ..... .. 44
3.2.2 System Kinematics. .... .... .... .... .... ..... .. 48
3.3 Control Algorithm ... ..... .... .... .... .... .... ..... .. 49
3.3.1 Baseline Shared-Control Algorithm .... .... ..... .. 49
3.3.2 Free-Space Mode and Contact Mode ... .... ..... .. 51
3.4 Application to the BOW ... .... .... .... .... .... ..... .. 54
3.4.1 User Interface..... .... .... .... .... .... ..... .. 54
3.4.2 Object Pick-Up and Placement Task.... .... ..... .. 55
3.4.3 Board Cleaning Task ... .... .... .... .... ..... .. 58
3.5 Conclusion. .... .... ..... .... .... .... .... .... ..... .. 60
References .. .... .... .... ..... .... .... .... .... .... ..... .. 61
4 Switchings Between Trajectory Tracking and Force
Minimization in Human–Robot Collaboration.. .... .... ..... .. 65
Yanan Li, Keng Peng Tee and Shuzhi Sam Ge
4.1 Introduction.... .... ..... .... .... .... .... .... ..... .. 65
4.2 Dynamic Models .... ..... .... .... .... .... .... ..... .. 67
4.2.1 Robot Model. ..... .... .... .... .... .... ..... .. 68
4.2.2 Human Arm Model .... .... .... .... .... ..... .. 68
4.2.3 Unified Model .... .... .... .... .... .... ..... .. 70
4.2.4 Trajectory Tracking .... .... .... .... .... ..... .. 71
4.3 Control Design.. .... ..... .... .... .... .... .... ..... .. 71
4.3.1 Control Objective.. .... .... .... .... .... ..... .. 71
4.3.2 Selection of Cost Functions .. .... .... .... ..... .. 72
4.3.3 Optimal Control ... .... .... .... .... .... ..... .. 73
4.4 Simulations .... .... ..... .... .... .... .... .... ..... .. 75
4.4.1 Simulation Settings. .... .... .... .... .... ..... .. 75
4.4.2 Change of Weights. .... .... .... .... .... ..... .. 76
4.4.3 Adaptation of Desired Trajectory .. .... .... ..... .. 78
4.5 Conclusions.... .... ..... .... .... .... .... .... ..... .. 79
Appendix: Proof of Lemma 4.1 ... .... .... .... .... .... ..... .. 79
References .. .... .... .... ..... .... .... .... .... .... ..... .. 80
5 Estimating Human Intention During a Human–Robot
Cooperative Task Based on the Internal Force Model.... ..... .. 83
Ehsan Noohi and Miloš Žefran
5.1 Introduction.... .... ..... .... .... .... .... .... ..... .. 83
5.2 Internal Force Model. ..... .... .... .... .... .... ..... .. 86
5.2.1 Problem Formulation ... .... .... .... .... ..... .. 86
Contents xiii
5.2.2 Existing Models ... .... .... .... .... .... ..... .. 87
5.2.3 Proposed Model ... .... .... .... .... .... ..... .. 88
5.2.4 Discussion .. ..... .... .... .... .... .... ..... .. 91
5.3 Method ... .... .... ..... .... .... .... .... .... ..... .. 91
5.3.1 Apparatus... ..... .... .... .... .... .... ..... .. 92
5.3.2 Procedure ... ..... .... .... .... .... .... ..... .. 92
5.4 Results.... .... .... ..... .... .... .... .... .... ..... .. 94
5.5 Validation of the Model.... .... .... .... .... .... ..... .. 97
5.6 Statistical Analysis of the Internal Force Features .... ..... .. 99
5.6.1 Initial Grasp Force Magnitude .... .... .... ..... .. 100
5.6.2 Final Grasp Force Magnitude. .... .... .... ..... .. 101
5.6.3 Internal Force Energy... .... .... .... .... ..... .. 101
5.6.4 Difference Between Initial and Final Grasp Forces.. .. 102
5.6.5 Internal Force Variation . .... .... .... .... ..... .. 102
5.6.6 Negotiation Force.. .... .... .... .... .... ..... .. 103
5.6.7 Negotiation Force Versus Object Velocity ... ..... .. 104
5.7 Proposed Cooperation Policy.... .... .... .... .... ..... .. 105
5.8 Conclusion. .... .... ..... .... .... .... .... .... ..... .. 107
References .. .... .... .... ..... .... .... .... .... .... ..... .. 108
6 A Learning Algorithm to Select Consistent Reactions
to Human Movements .... ..... .... .... .... .... .... ..... .. 111
Carol Young and Fumin Zhang
6.1 Introduction.... .... ..... .... .... .... .... .... ..... .. 111
6.2 Background .... .... ..... .... .... .... .... .... ..... .. 113
6.2.1 Expert-Based Learning.. .... .... .... .... ..... .. 113
6.2.2 Binary Learning Algorithms.. .... .... .... ..... .. 114
6.3 Analysis... .... .... ..... .... .... .... .... .... ..... .. 115
6.3.1 Performance . ..... .... .... .... .... .... ..... .. 116
6.3.2 Consistency . ..... .... .... .... .... .... ..... .. 116
6.3.3 Adaptiveness. ..... .... .... .... .... .... ..... .. 118
6.3.4 Tie Breaking. ..... .... .... .... .... .... ..... .. 119
6.4 Expanded Dual Expert Algorithm .... .... .... .... ..... .. 120
6.4.1 Performance Analysis... .... .... .... .... ..... .. 121
6.4.2 Consistency and Adaptiveness .... .... .... ..... .. 122
6.5 Simulation . .... .... ..... .... .... .... .... .... ..... .. 122
6.5.1 Dual Expert Algorithm.. .... .... .... .... ..... .. 122
6.5.2 Expanded Dual Expert Algorithm.. .... .... ..... .. 123
6.6 Experiment. .... .... ..... .... .... .... .... .... ..... .. 125
6.6.1 Setup .. .... ..... .... .... .... .... .... ..... .. 126
6.6.2 Results . .... ..... .... .... .... .... .... ..... .. 127
6.7 Conclusions.... .... ..... .... .... .... .... .... ..... .. 129
References .. .... .... .... ..... .... .... .... .... .... ..... .. 129