A COGNITIVE APPROACH TO MOBILE ROBOT ENVIRONMENT MAPPING AND PATH PLANNING Peter J. Zeno Under the Supervision of Dr. Tarek Sobh and Dr. Sarosh Patel DISSERTATION SUBMITTED IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY IN COMPUTER SCIENCE AND ENGINEERING THE SCHOOL OF ENGINEERING UNIVERSITY OF BRIDGEPORT CONNECTICUT May, 2017 A COGNITIVE APPROACH TO MOBILE ROBOT ENVIRONMENT MAPPING AND PATH PLANNING Peter J. Zeno Under the Supervision of Dr. Tarek Sobh and Dr. Sarosh Patel Approvals Committee Members Name Signature Date Dr. Tarek Sobh __________________________ __________ Dr. Sarosh Patel __________________________ __________ Dr. Miad Faezipour __________________________ __________ Dr. Prabir Patra __________________________ __________ Dr. Nicolas Cuperlier __________________________ __________ Ph.D. Program Coordinator Dr. Khaled M. Elleithy __________________________ __________ Chairman, Computer Science and Engineering Department Dr. Ausif Mahmood __________________________ __________ Dean, School of Engineering Dr. Tarek M. Sobh __________________________ __________ ii A COGNITIVE APPROACH TO MOBILE ROBOT ENVIRONMENT MAPPING AND PATH PLANNING © Copyright by Peter Zeno 2017 iii A COGNITIVE APPROACH TO MOBILE ROBOT ENVIRONMENT MAPPING AND PATH PLANNING ABSTRACT This thesis presents a novel neurophysiological based navigation system which uses less memory and power than other neurophysiological based systems, as well as traditional navigation systems performing similar tasks. This is accomplished by emulating the rodent’s specialized navigation and spatial awareness brain cells, as found in and around the hippocampus and entorhinal cortex, at a higher level of abstraction than previously used neural representations. Specifically, the focus of this research will be on replicating place cells, boundary cells, head direction cells, and grid cells using data structures and logic driven by each cell’s interpreted behavior. This method is used along with a unique multimodal source model for place cell activation to create a cognitive map. Path planning is performed by using a combination of Euclidean distance path checking, goal memory, and the A* algorithm. Localization is accomplished using simple, low power sensors, such as a camera, ultrasonic sensors, motor encoders and a gyroscope. The place code data structures are initialized as the mobile robot finds goal locations and other unique locations, and are then linked as paths between goal locations, as goals are found during exploration. The place code creates a hybrid cognitive map of metric and topological data. In doing so, iv much less memory is needed to represent the robot’s roaming environment, as compared to traditional mapping methods, such as occupancy grids. A comparison of the memory and processing savings are presented, as well as to the functional similarities of our design to the rodent’ specialized navigation cells. v ACKNOWLEDGEMENTS My deepest gratitude goes to my family, friends and educators who have blessed me with their support along this incredible journey. For without their encouragement and enlightenment, such a journey would not have been possible. Thank you, Dad, for always being there for me and for your unquestioning support. Your insight and stories related to animal navigation behavior have always been inspirational and thought provoking. I am honored to have had the opportunity to work under the supervision of Dr. Tarek Sobh and Dr. Sarosh Patel. I am fortunate to have been guided by Dr. Sobh in my thesis topic. For he believed in my vision and allowed for me to follow a topic that was along a path less traveled. Additionally, I greatly appreciate the real-world advice and continued guidance I receive from Dr. Patel. I would like to sincerely thank Dr. Miad Faezipour, Dr. Prabir Patra and Dr. Nicolas Cuperlier for accepting to be members of my dissertation committee. I greatly appreciate their time and efforts in the review of my work, taking part in my defenses, and giving incredibly valuable feedback. Finally, I would like to express my deepest gratitude to my best friend Roberta Voss for her company and loving support that always kept me motivated. vi TABLE OF CONTENTS ABSTRACT ............................................................................................................... iv ACKNOWLEDGEMENTS ....................................................................................... vi TABLE OF CONTENTS .......................................................................................... vii LIST OF TABLES ...................................................................................................... x LIST OF FIGURES .................................................................................................... xi ACRONYMS ........................................................................................................... xiii GLOSSARY .............................................................................................................. xv CHAPTER 1: INTRODUCTION................................................................................ 1 1.1 Research Problem and Scope ............................................................................. 1 1.2 Motivation .......................................................................................................... 3 1.3 Contributions ..................................................................................................... 4 CHAPTER 2: SPATIAL AWARENESS IN RODENTS ........................................... 6 2.1 Specialized Navigation and Spatial Awareness Rodent Brain Cells ................. 6 2.1.1 Place Cells ................................................................................................... 7 2.1.2 Head Direction Cells ................................................................................... 8 2.1.3 Boundary Cells ............................................................................................ 8 2.1.4 Grid Cells .................................................................................................... 8 2.2 Path Integration .................................................................................................. 9 2.3 Review of Rodent Spatial Awareness and Navigation Models ....................... 10 2.3.1. Arleo and Gerstner 2000 .......................................................................... 11 vii 2.3.2. Fleischer et al. 2007 ................................................................................. 14 2.3.3. Strösslin et al. 2005 .................................................................................. 16 2.3.4. Hafner 2008.............................................................................................. 18 2.3.5. Barrera and Weitzenfeld 2008 ................................................................. 19 2.3.6. Wyeth and Milford: RatSLAM, Version 3 .............................................. 22 2.3.7. Cuperlier et al. 2007 ................................................................................. 24 2.3.8. Grid Cell Centric Systems ........................................................................ 28 2.4 Analysis of Reviewed Systems’ Localization ................................................. 31 CHAPTER 3: SENSORY INPUT ............................................................................. 35 3.1 Idiothetic Sensors for Path Integration Model ................................................. 35 3.1.1 Heading Sensor ......................................................................................... 37 3.1.2 Motor Encoders ......................................................................................... 39 3.2 Allothetic Sensors ............................................................................................ 39 3.2.1 Ultrasonic Range Sensors ......................................................................... 39 3.2.1 Visual System ........................................................................................... 42 CHAPTER 4: NEW MULTIMODAL PLACE CELL MODEL .............................. 45 4.1 Multimodal Place Cell Model Basics .............................................................. 45 4.2 Logical Architecture of Multimodal Place Cell Model ................................... 45 CHAPTER 5: NAVIGATION SYSTEM IMPLEMENTATION ............................. 49 5.1 Hardware System Design ................................................................................. 49 viii 5.2 Software Design ............................................................................................... 51 5.3 FPGA Design ................................................................................................... 57 CHAPTER 6: LOCALIZATION AND PATH PLANNING .................................... 59 6.1 Localization ..................................................................................................... 60 6.1.1 Level of Confidence Calculation .............................................................. 61 6.1.2 Localization Accuracy .............................................................................. 62 6.1.3 Place and Boundary Field Initialization Accuracy ................................... 62 6.2 Route Planning ................................................................................................. 64 CHAPTER 7: SUMMARY & FUTURE DIRECTIONS .......................................... 67 7.1