Navigation, Path Planning, and Task Allocation Framework For Mobile Co-Robotic Service ...

201 Pages·2017·3.23 MB·English

by  Bharadwaj Mantha

Navigation, Path Planning, and Task Allocation Framework For Mobile Co-Robotic
Service Applications in Indoor Building Environments

by

Bharadwaj Mantha

A dissertation submitted in partial fulfillment of
the requirements for the degree of
Doctor of Philosophy
(Civil Engineering)
in the University of Michigan
2018

Doctoral Committee:
Associate Professor Carol C. Menassa, Chair
Assistant Professor Clive D’Souza
Professor Vineet R. Kamat
Associate Professor SangHyun Lee
Bharadwaj Mantha
[email protected]
ORCID iD: 0000-0002-3173-3966
© Bharadwaj Mantha 2018
DEDICATION
I would like to dedicate this dissertation to my loving and caring parents (Bhavani Shankar
Mantha and Suryakumari Peri), wife (Ramani Ayyagari), brother (Dheeraj Mantha), and in laws
(Srinivas Rao Ayyagari and Padmavathi Ayyagari).

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ACKNOWLEDGMENTS
I would like to express my sincere gratitude to my advisor Dr. Carol Menassa for all the support
and guidance throughout my PhD. Her ever smiling face made me feel comfortable right from
the moment I met her. I found her to be uniquely capable of capturing my attention and helping
me learn confidently. She was always supportive, optimistic and encouraging in all the
encounters. I have learned a great deal from her especially hardworking, professional etiquette,
academic writing skills, presentation skills, and most importantly the technical expertise to name
a few.
I would be deeply indebted to Dr. Vineet Kamat who I closely collaborated with since the
beginning of my graduate studies. His passion for research, simplicity, patience, and technical
abilities helped me polish my skills. I will never forget the conversations I had with him during a
few successful and challenging phases of my PhD. It has been an honor working with him.
I also want to thank the rest of my committee members Dr. SangHyun Lee and Dr. Clive
D’Souza. Especially, Dr. Lee’s constructive feedback during my proposal defense to improve the
technical and logical continuity of my thesis was invaluable. In addition, the wheelchair
navigation study wouldn’t have been possible without Dr. D’Souza’s guidance and suggestions. I
would also like to specially thank Dr. Branko Kerkez for having inspired me with his out of the
box approach during my preliminary examination.
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I also thank my lab mates (SICIS’ers and LIVE’ers) Albert Thomas, Kurt Lundeen, Yong Xiao,
Da Li, Chen Feng, Lichao Xu, Xi Wang, for round the clock advice, sleepless working nights,
and for all the fun we had in the past few years.
Last but definitely not the least I would like to thank all the members of my family and friends
who directly or indirectly made this possible.

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TABLE OF CONTENTS

DEDICATION ................................................................................................................................ ii
ACKNOWLEDGMENTS ............................................................................................................. iii
LIST OF TABLES ....................................................................................................................... viii
LIST OF FIGURES ....................................................................................................................... ix
LIST OF APPENDICES .............................................................................................................. xiv
ABSTRACT .................................................................................................................................. xv
Chapter 1 Introduction .................................................................................................................... 1
1.1 Background and Literature Review.................................................................................. 2
1.1.1 Task Allocation and Route Planning ........................................................................ 2
1.1.2 Localization and Navigation ..................................................................................... 4
1.1.3 Path Planning ............................................................................................................ 6
1.2 Research Objectives ......................................................................................................... 9
1.3 Research Methodology ..................................................................................................... 9
1.4 Dissertation Outline........................................................................................................ 11
Chapter 2 Planning and Coordination Algorithms for Indoor Robotic Service Networks ........... 13
2.1 Introduction ......................................................................................................................... 13
2.2 Related Work....................................................................................................................... 17
2.3 Problem Statement And Characteristics .............................................................................. 20
2.4 Methodology ....................................................................................................................... 22
2.4.1 Network formulation .................................................................................................... 22
2.4.2 Network Solution .......................................................................................................... 30
2.5 Case Study ........................................................................................................................... 45
2.5.1 Scenario 1: No Constraints ........................................................................................... 46
2.5.2 Scenario 2: Distance Constraints .................................................................................. 48
2.5.3 Scenario 3: Tasks Requirements, Frequency, and Resource (Robots) Constraints ...... 50
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2.5.4 Scenario 4: Occlusion Constraints ................................................................................ 50
2.6 Results And Discussion ....................................................................................................... 51
2.6.1 Scenario 1 ..................................................................................................................... 51
2.6.2 Scenario 2 ..................................................................................................................... 55
2.6.3 Scenario 3 ..................................................................................................................... 57
2.6.4 Scenario 4 ..................................................................................................................... 60
CONCLUSIONS ....................................................................................................................... 61
Chapter 3 Localization and Navigation Algorithms for Indoor Robotic Data Collection and
Simulation ..................................................................................................................................... 64
3.1 Introduction ......................................................................................................................... 64
3.2 Review Of Data Collection Methods In Buildings ............................................................. 66
3.3 Research Objectives ............................................................................................................ 68
3.4 Design Of The Mobile Robot .............................................................................................. 69
3.5 Methodology ....................................................................................................................... 71
3.5.1 Localization .................................................................................................................. 72
3.5.2 Navigation .................................................................................................................... 80
3.5.3 Data Collection and Geotagging................................................................................... 90
3.6 Verification.......................................................................................................................... 91
3.6.1 Localization .................................................................................................................. 91
3.6.2 Navigation .................................................................................................................... 92
3.6.3 Data Collection ............................................................................................................. 95
3.6.4 Geotagging.................................................................................................................... 96
3.7 Case Study ........................................................................................................................... 97
3.7.1 Model Creation ............................................................................................................. 99
3.7.2 Model Calibration ....................................................................................................... 103
3.7.3 Simulation Output and Analysis ................................................................................. 104
3.8 Discussion, Conclusions And Limitations ........................................................................ 106
Chapter 4 Usability Evaluation of a User Interface based on a Preferential Path Planning
Algorithm for Assisting Individuals with Disabilities in Indoor Building Environments .......... 109
4.1 Introduction ....................................................................................................................... 109
4.2 Background ....................................................................................................................... 112
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4.3 Methodology ..................................................................................................................... 115
4.3.1 Attribute Loaded Graph Network ............................................................................... 116
4.3.2 Attribute Sensitive Path Planning ............................................................................... 122
4.3.3 Fiducial Marker Network ........................................................................................... 125
4.3.4 Communication .......................................................................................................... 132
4.4 Case Study ......................................................................................................................... 141
4.4.1 Scenario 1: Preferential Constraints (shortest vs least number of turns) .................... 142
4.4.2 Scenario 2: Add Stop .................................................................................................. 143
4.4.3 Scenario 3: Detour Management ................................................................................ 144
4.4.4 Scenario 4: Missed Marker ......................................................................................... 144
4.5 Pilot Testing Of The Navigation Application ................................................................... 146
4.5.1 Phase I: Training with the wheelchair and application interface ................................ 148
4.5.2 Phase II: Actual navigation tasks................................................................................ 148
4.5.3 Phase III: Basic Survey and Post-trial interview ........................................................ 149
4.6 Results ............................................................................................................................... 151
4.7 Conclusions ....................................................................................................................... 154
Chapter 5 Conclusions and Future Work .................................................................................... 156
5.1 Future Directions of Research ........................................................................................... 159
5.1.1 Multi-Base Depot Optimization for Indoor Robotic Service Networks ..................... 159
5.1.2 Sensor Suite Design for Robotic Data Collection ...................................................... 159
5.1.3 Data Fusion, Aggregation, and Visualization of Data Collected by Robots .............. 160
APPENDICES ............................................................................................................................ 161
BIBLIOGRAPHY ....................................................................................................................... 167

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LIST OF TABLES
Table 2.1 Characteristics of the problem statement ...................................................................... 19
Table 2.2 Limitations of the existing studies ................................................................................ 19
Table 2.3. Simulation results without any constraints for floor plan-1 ........................................ 52
Table 2.4 Simulation results without any constraints for floor plan-2 ......................................... 53
Table 2.5 Simulation results with minimum and maximum distance constraints for floor plan-2
With Minimum (30 units) and Maximum (70 units) Distance Constraints .................................. 56
Table 2.6 Interdependency between the number of robots and the frequency of task
accomplishment (applied with distance constraints) for floor plan-2. .......................................... 59
Table 3.1 Experimental results to determine the marker to marker distance ................................ 94
Table 3.2 Experimental results validating the drift correction algorithm developed. .................. 95
Table 3.3 Characteristics of the case study building..................................................................... 99
Table 3.4 R-value estimation for individual materials. ............................................................... 101
Table 3.5 Conductivity value estimation for individual materials by assuming a building age of
20 years and K value as 40%. ..................................................................................................... 102
Table 3.6 Comparison of simulated (EnergyPlus) and actual (robot) ambient temperature values.
..................................................................................................................................................... 104
Table 3.7 EnergyPlus output results for multiple retrofit scenarios ........................................... 105
Table 4.1 Functional requirements of an assistive navigation interface for individuals with
disabilities ................................................................................................................................... 132
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LIST OF FIGURES
Figure 1.1 Research Overview (Topics and Applications) ................................................................. 11
Figure 2.1 Detailed descriptive procedure of the proposed methodology .................................... 24
Figure 2.2 Multilayer information generation and simultaneous storage of graph network data
(i.e. creating the network): (a) task requirement layer (data collection locations); (b) landmark
network layer (for localization/navigation); (c) reduced node network layer .............................. 27
Figure 2.3 (a) Complete graph network with four nodes; (b) random incomplete network; (c)
random incomplete graph network converted to a complete graph by including pseudo edges .. 28
Figure 2.4 Graphical representation of the conversion from created network (reduced incomplete
node network) to setting up the network (complete network): (a) reduced graph node network
layer; (b) undirected incomplete graph network (G = V, E); (c) complete graph network with
pseudo edges (dashed) .................................................................................................................. 29
Figure 2.5 Two-dimensional graph network representation of indoor multilevel building network
....................................................................................................................................................... 30
Figure 2.6 Methodical process to find the shortest path for a single robot to visit all the nodes in a
graph (at least once): (a) complete graph network with pseudo edges (dashed); (b) shortest path
to visit all the nodes with a single robot (dashed lines represent pseudo edges); (c) shortest path
to visit all the nodes with a single robot ....................................................................................... 32
Figure 2.7 Process flow for solving the multi-robot task allocation and path planning problem . 35
Figure 2.8 Edge representation of an example indoor network .................................................... 36
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