DTIC ADA474020: An Adaptive Planning Framework for Situation Assessment and Decision-Making on an Autonomous Ground Vehicle

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AN ADAPTIVE PLANNING FRAMEWORK FOR SITUATION ASSESSMENT AND
DECISION-MAKING ON AN AUTONOMOUS GROUND VEHICLE

By

ROBERT ALLEN TOUCHTON

A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
DOCTOR OF PHILOSOPHY

UNIVERSITY OF FLORIDA

2006
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1. REPORT DATE 3. DATES COVERED
2006 2. REPORT TYPE 00-00-2006 to 00-00-2006
4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER
An Adaptive Planning Framework for Situation Assessment and
5b. GRANT NUMBER
Decision-Making on an Autonomous Ground Vehicle
5c. PROGRAM ELEMENT NUMBER
6. AUTHOR(S) 5d. PROJECT NUMBER
5e. TASK NUMBER
5f. WORK UNIT NUMBER
7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) 8. PERFORMING ORGANIZATION
University of Florida,Center for Intelligent Machines and Robotics,P.O. REPORT NUMBER
Box 116300,Gainesville,FL,32611
9. SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES) 10. SPONSOR/MONITOR’S ACRONYM(S)
11. SPONSOR/MONITOR’S REPORT
NUMBER(S)
12. DISTRIBUTION/AVAILABILITY STATEMENT
Approved for public release; distribution unlimited
13. SUPPLEMENTARY NOTES
14. ABSTRACT
The primary contribution of this research is the design, implementation, and field testing of an Adaptive
Planning Framework (APF) that can address the problem of autonomous operation in a complex,
unstructured environment. It encapsulates a new and unique approach to dynamic situation assessment,
behavior management, and decision-making. This research also included a literature review and
development of a Reference Implementation. The thesis behind this research is that a well-organized,
three-stage process of 1) understanding the current situation, 2) understanding the suitability and viability
of the available behaviors in light of that situation, and 3) providing the capability to autonomously make
and execute behavior-related decisions, all in real-time, provides new levels of intelligence to autonomous
ground vehicles (AGV). This research was performed using the resources of the UF Center for Intelligent
Machines and Robotics. This environment provided the ability to collaboratively explore engineering
alternatives, create experimental software, and test it in a real-world setting, ultimately leading to the
creation of the Reference Implementation. All this was aimed at validating the thesis of the research and
producing a more robust APF, operationally proven in a representative physical environment. The
Adaptive Planning Framework has been shown to be both a viable method for representing and managing
complex, situation-dependent behavior on an AGV and a valuable contribution to researchers tasked with
developing and fielding such a vehicle. The viability of the architecture and design was demonstrated by
the development and testing of the Reference Implementation. The value of the APF can be measured by
the major role it is playing in the architecture and design of the AGV being fielded by Team Gator Nation
for competing in the 2007 DARPA Urban Challenge. The Adaptive Planning Framework makes a
significant contribution to advancing the state of the practice of intelligent systems in general and AGVs in
particular. Its adoption by Team Gator Nation means that it will be improved and extended by future
researchers. Presuming that occurs, this work will have been the catalyst of a new way of achieving more
intelligent and more autonomous ground vehicles.
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Copyright 2006

by

Robert Allen Touchton

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To Cheryle
My biggest fan since High School
My wife for 35 years (and counting)
My soul mate for eternity

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ACKNOWLEDGMENTS
First and foremost, I thank my family not only for their support and tolerance, but also for
their enthusiasm and interest in this endeavor. I also appreciate the prayers and tender loving
care that my church family provided, both in Jacksonville and Gainesville. They helped me
maintain and balance my priorities.
Many, many years ago, when I first conceived the ideas that evolved into the Adaptive
Planning Framework, I was working with an amazing team of engineers and software
developers. I especially want to thank Dale Gunter, Steve Rausch, and Ken Wilson for their help
in getting these ideas out of my head and into a sound, working system.
I would also like to acknowledge the sponsorship and support provided by CIMAR, the Air
Force Research Lab, Team CIMAR, and Team Gator Nation that made this research possible. I
must add specific recognition of the significant help and support I received from my fellow
Graduate Research Assistants Tom Galluzzo, Greg Garcia, Danny Kent, Sanjay Solanki, Eric
Thorn, and Steve Velat. I also appreciate the excellent editorial review provided by Michelle
LaMontagne.
Finally, I want to extend a special word of thanks to key reviewers of my work, David
Armstrong, Dr. Douglas Dankel, Shannon Ridgeway, and Dr. Eric Schwartz, and, of course, to
my committee, Dr. Carl Crane, Dr. Tony Arroyo, Dr. Warren Dixon, Dr. Gloria Wiens, and Dr.
Charles Winton. Their critiques and ideas were helpful and made a real difference in my work. I
add an additional expression of appreciation to Dr. Crane, who welcomed me into the CIMAR
autonomous vehicle program and then mentored me through it.

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TABLE OF CONTENTS

page
ACKNOWLEDGMENTS...............................................................................................................4
LIST OF TABLES...........................................................................................................................8
LIST OF FIGURES.........................................................................................................................9
OBJECT.........................................................................................................................................10
ABSTRACT...................................................................................................................................11
CHAPTER
1 INTRODUCTION..................................................................................................................13
Motivation and Statement of Problem....................................................................................13
Research Solution...................................................................................................................14
Research Setting.....................................................................................................................16
2 BACKGROUND AND LITERATURE REVIEW................................................................21
Architectural Compatibility with Emerging Standards..........................................................21
JAUS RA.........................................................................................................................21
NIST 4D/RCS..................................................................................................................23
Service Oriented Architecture/Component Oriented Architecture.................................24
DAMN.............................................................................................................................26
Situation Assessment..............................................................................................................27
Planning and Decision-making...............................................................................................29
Viewed as a Sense-Plan-Act Problem.............................................................................30
Viewed as a Subsumption Problem.................................................................................32
Viewed as a Decision Theory Problem...........................................................................33
Viewed as a Behavior Arbitration Problem.....................................................................35
Viewed as an Action Selection Problem.........................................................................36
Viewed as an Adaptive Planning Problem......................................................................37
Knowledge Representation.....................................................................................................39
Lexicons, Taxonomies and Ontologies...........................................................................40
World Model Knowledge Store (WMKS)......................................................................41
Knowledge Representation at NIST................................................................................42
3 THE ADAPTIVE PLANNING FRAMEWORK...................................................................50
Knowledge Representation Scheme.......................................................................................50
Situation Assessment Specialists.....................................................................................53
Behavior Specialists........................................................................................................53
Decision Specialist..........................................................................................................55
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Reasoning Mechanism............................................................................................................56
Concept of Operation......................................................................................................57
Transmission of Findings................................................................................................58
Knowledge Representation Tools...........................................................................................59
Behavior Use Cases.........................................................................................................59
Findings Worksheet.........................................................................................................61
Decision Broker Protocol Worksheet..............................................................................63
Foundational Research............................................................................................................64
4 REFERENCE IMPLEMENTATION AND FIELD TESTING.............................................72
Reference Implementation Architecture and Design..............................................................72
Behaviors Identified........................................................................................................72
Specialists and Findings Identified..................................................................................73
Decision Protocols Identified..........................................................................................75
Reference Implementation Messaging Design.......................................................................76
JAUS-based Meta Data Message Set..............................................................................77
Extensions to CIMAR Messaging Infrastructure............................................................79
Reference Implementation Development...............................................................................81
Modifications to Existing NAVIGATOR Components....................................................82
Creation of New Components.........................................................................................83
Field Testing...........................................................................................................................84
Test Plans.........................................................................................................................84
Test Results.....................................................................................................................87
5 DISCUSSION AND FUTURE WORK.................................................................................94
Assessment of the Adaptive Planning Framework.................................................................94
Future Work............................................................................................................................95
Theoretical Opportunities................................................................................................95
Implementation Opportunities.........................................................................................98
Conclusion............................................................................................................................100

APPENDIX
A PROOF OF CONCEPT PROTOTYPE................................................................................102
Scope of Prototype................................................................................................................102
Approach...............................................................................................................................103
Concept of Operations..........................................................................................................103
Issues Identified....................................................................................................................105
Algorithm and Program Logic Flow.....................................................................................106
Inferencing Control Strategy and User Interface...........................................................106
Truth Maintenance.........................................................................................................106
Retraction of Conditions................................................................................................107
Predicate Testing in Rule Antecedents..........................................................................108
Testing Results......................................................................................................................109
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Test Case Scenario Set-up.............................................................................................109
Rule Base................................................................................................................109
Blackboard initialization........................................................................................111
Condition defaults..................................................................................................111
Test Cases and Results..................................................................................................111
Test Case 1 – initial resolution of Blackboard at time = 0.....................................111
Test Case 2a – Rugged Terrain is encountered......................................................112
Test Case 2b – Rugged Terrain no longer present.................................................114
Test Case 3a – long range obstacle detection.........................................................115
Test Case 3b – close range obstacle detection.......................................................116
Test Case 3c – obstacle avoided.............................................................................117
B EARLY IMPLEMENTATION AND DESERT TESTING ON THE 2005 DARPA
GRAND CHALLENGE NAVIGATOR..............................................................................120
Test Case Scenario Set-up....................................................................................................121
Desert Testing and Results...................................................................................................122
C KNOWLEDGE REPRESENTATION WORK PRODUCTS FOR THE ADAPTIVE
PLANNING FRAMEWORK REFERENCE IMPLEMENTATION..................................126
D JAUS META DATA TRANSFER INTERFACE CONTROL DOCUMENT....................143
E REPRESENTATIVE TEST LOGS......................................................................................151
LIST OF REFERENCES.............................................................................................................159
BIOGRAPHICAL SKETCH.......................................................................................................163

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LIST OF TABLES
Table page

3-1 Example Assignment of Situation Assessment Specialists...............................................65
4-1 JAUS Type Codes Supported by JausVariant Data Type..................................................89
A-1 Environmental Sensors....................................................................................................119
A-2 Vehicle Sensors................................................................................................................119
A-3 Mission Information.........................................................................................................119
A-4 Vehicle Specialist.............................................................................................................119
A-5 Sensor Specialist (States).................................................................................................119
A-6 Sensor Specialist (Conditions).........................................................................................119
A-7 Mission Specialist............................................................................................................119
B-1 Environmental Sensor......................................................................................................124
B-2 Vehicle Sensor.................................................................................................................124
B-3 Obstacle Specialist...........................................................................................................124
B-4 Terrain Specialist.............................................................................................................124
B-5 Decision Broker...............................................................................................................125

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