Calhoun: The NPS Institutional Archive Theses and Dissertations Thesis Collection 1992-03 NPS AUV Integrated Simulation Brutzman, Donald P. Monterey, California. Naval Postgraduate School http://hdl.handle.net/10945/26108 NAVAL POSTGRADUATE SCHOOL Monterey, California THESIS NPS AUV INTEGRATED SIMULATOR by Donald P. Brutzman March, 1992 Thesis Advisors: Yutaka Kanayama Michael J. Zyda Approved for public release; distribution is unlimited. T2568 01 REPORT DOCUMENTATION PAGE fa REPORT SECURITY CLASSIFICATION UNCLASSIFIED lb. RESTRICT IVE MARKING *a SECURITY CLASSIFICATION AUTHORITY 3. DISTRIBU TION/AVAILABILI TY OF REPORT Approved for public release; lb. DECLASSIFICATION/DOWNORADlNO SCHEDULE distribution is unlimited PERFORMING ORGANIZATION REPORT NUMBER(S) 5 MONITORING ORGANIZATION REPORT NUMBER(S) 1 .. NAME OF I ERFORMING ORGANIZATION 6b. OFFICE SYMBOL 7a. NAME OF MONITORING ORGANIZATION S-omputer Sciencei Dept. (if applicable) Naval Postgraduate School Naval Postgraduate School cs 3c. ADDRESS (City, State, and ZIP Code) 7b. ADDRESS (City, State, and ZIP Code) Monterey, CA 93943-5000 Monterey, CA 93943-5000 3a. NAME OF FUNDING/SPONSORING OFFIC E SYMBOL PROCUREMENT INSTRUMENT IDENTIFICATION NUMBER ORGANIZATION (if applicable) 3c. ADDRESS (City, State, and ZIP Code) 10. SOURCE OF FUNDING NUMBERS - PROGRAM I PROJECT TASK WORK UNIT ELEMENT NO NO. NO. ACCESSION NO 11. TITLE (Include Security Classification) NPS AUV INTEGRATED SIMULATOR 1 1 PERSONAL AUTHOR(S) Donald P. Brutzman I3a. TYPE OF REPORT 1 3b. TIME COVERED 14. DATE OF REPORT (Year, Month, Day) 15. PACE COUNT Master's Thesis from 04/90 to 03/92 1992, March, 17 269 supplementary notation 6. Tj-, e views expressed in this thesis are those of the author and do not reflect the official policy or position of the Department of Defense or the United States Government. COSATI CODES 18 SUBJECT TERMS (Continue on reverse if necessary and identify by block number) Autonomous Underwater Vehicles, Graphics, Simulation, Path Planning, FIELD SUB-GROUP Sonar Classification, Expert Systems, Real-Time Operating Systems. 9. ABSTRACT (Continue on reverse if necessary and identify by block number) The development and testing of Autonomous Underwater Vehicle (AUV) hardware and software is gready complicated by :hicle inaccessibility during operation. Integrated simulation remotely links vehicle components and support equipment with aphics simulation workstations, allowing complete real-time, pre-mission, pseudo-mission and post-mission visualization in e lab environment. Integrated simulator testing of software and hardware is a broad and versatile method that supports rapid d robust diagnosis and correction of system faults. This method is demonstrated using the NPS AUV. High-resolution three-dimensional graphics workstations can provide real-time representations of vehicle dynamics, control 5 stem behavior, mission execution, sensor processing and object classification. Integrated simulation is also useful for velopment of the variety of sophisticated artificial intelligence applications needed by an AUV. Examples include nar classification using an expert system and path planning using a circle world model. The flexibility and versatility provided by this approach enables visualization and analysis of all aspects of AUV (jvelopment. Integrated simulator networking is recommended as a fundamental requirement for AUV research and ( velopment. ). DIST RIBU T ION/AVAILABIL IT Y OF ABST RAC T 2i. ABST RAC T SECUR ITY CLASSIFICA TION UNCLASSIFIED/UNLIMITED SAME AS RPT. DTIC USERS 1] fjj [J UNCLASSIFIED ME OF RESPONSIBLE INDIVIDUAL. 22b. TELEPHONEtfnc/ucfe Area Code) E SYMBOL I Yutaka Kanayama and Dr. Michael J. Zyda (408) 646-2095/2305 It FORM 1473, 84 MAR 83 APR edition may be used until exhausted SECURITY CLASSIFICATION OF THIS PAGE All other editions are obsolete UNCLASSIFIED Approved for public release; distribution is unlimited. NPS AUV INTEGRATED SIMULATOR by Donald P. Brutzman Lieutenant Commander, United States Navy B.S.E.E., United States Naval Academy, 1978 Submitted in partial fulfillment of the requirements for the degree of MASTER OF COMPUTER SCIENCE from the NAVAL POSTGRADUATE SCHOOL March 1992 ABSTRACT The development and testing of Autonomous Underwater Vehicle (AUV) hardware and software is greatly complicated by vehicle inaccessibility during operation. Integrated simulation remotely links vehicle components and support equipment with graphics simulation workstations, allowing complete real-time, pre-mission, pseudo-mission and post-mission visualization and analysis in the lab environment. Integrated simulator testing of software and hardware is a broad and versatile method that supports rapid and robust diagnosis and correction of system faults. This method is demonstrated using the Naval Postgraduate School (NPS) AUV. High-resolution three-dimensional graphics workstations can provide real-time representations of vehicle dynamics, control system behavior, mission execution, sensor processing and object classification. Integrated simulation is also useful for development of the variety of sophisticated artificial intelligence applications needed by an AUV. Examples include sonar classification using an expert system and path planning using a circle world model. The flexibility and versatility provided by this approach enables visualization and analysis of all aspects of AUV development. Integrated simulator networking is recommended as a fundamental requirement for AUV research and deployment. in 1 1. TABLE OF CONTENTS I. INTRODUCTION 1 A. PROBLEM STATEMENT 1 B. MOTIVATION 2 C. OBJECTIVES 3 D. THESIS ORGANIZATION 4 II. AUV RESEARCH AT THE NAVAL POSTGRADUATE SCHOOL 7 A. IMPORTANCE OF AUVs IN NAVAL MISSIONS 7 B. NPS AUV DESIGN SPECIFICATION SUMMARY 8 C. NPS AUV RESEARCH OBJECTIVES 10 D. THE FUTURE OF NAVAL AUVs 16 III. INTEGRATED SIMULATION FOR RAPID AUV DEVELOPMENT 18 A. ABSTRACT 18 B. INTRODUCTION 19 1. Problem Statement 19 2. Motivation 19 3. Definition and Objectives of Integrated Simulation 20 4. Previous Work 20 C. AUV DESIGN AND DEVELOPMENT CONSIDERATIONS 22 1. AUV Inaccessibility During Operation 22 2. Reliability is Paramount 23 3. Wide Variety of Software Process Types 23 D. INTEGRATED SIMULATOR SOFTWARE ARCHITECTURE 24 1. Software Engineering Considerations 24 2. Integrated Simulator Software Architecture Requirements 24 3. Simulated and Actual Components 24 4. Data Transfer Mechanisms 26 5. Distributed Artificial Intelligence Considerations 29 E. THREE-DIMENSIONAL GRAPHICS SIMULATION 30 1. Realistic Object Rendering and Real-Time Motion 30 2. Physical Modeling 30 3. Sonar and Sensor Visualization 31 F. INTEGRATED SIMULATOR HARDWARE ARCHITECTURE 31 1. Workstation Compatibility 31 2. External Network Connectivity 32 G. IMPLEMENTATION, EVALUATION AND EXPERIMENTAL RESULTS 32 1. NPS AUV Vehicle Description and Sonar Characteristics 32 2. NPS AUV Integrated Simulator 33 3. Silicon Graphics IRIS Workstation Capabilities 36 4. Laboratory AUV Simulation 36 H. ADDITIONAL APPLICATIONS 37 1. Sonar Classification Application 37 2. Circle World Path Planning Application 38 3. Minefield Search Application 39 I. ADDITIONAL APPLICABILITY, LIMITATIONS AND FUTURE WORK 39 1. Comparison of Theoretical and Empirical Data 39 2. Limitations to Integrated Simulation 40 3. Future Use of Integrated Simulation 41 J. CONCLUSIONS 41 IV. NPS AUV INTEGRATED SIMULATOR DESIGN SPECIFICATIONS 42 A. NPS AUV ACTIVE SONAR SYSTEM 42 B. NPS POOL COORDINATE SYSTEM 44 C. NPS AUV TELEMETRY REPLAY FILE FORMAT 46 D. SOFTWARE PROCESS SPECIFICATIONS 47 E. CONCLUSIONS 48 V. NPS AUV INTEGRATED SIMULATOR DATA NETWORK 50 A. INTEGRATED SIMULATOR DATA NETWORK OBJECTIVES 50 B. NETWORK CONNECTIVITY REQUIREMENTS AND ETHERNET . 50 C. NETWORK HARDWARE REQUIREMENTS 53 D. OPERATING SYSTEM INTERFACES 59 E. CONCLUSIONS 60 VI. AUTONOMOUS SONAR CLASSIFICATION USING EXPERT SYSTEMS . 62 A. ABSTRACT 62 B. INTRODUCTION 63 C. OVERVIEW 64 D. GEOMETRIC ANALYSIS OF SONAR DATA 66 1. General Characteristics of Active Sonar Data 66 2. Geometric Primitives and Object Attribute Definitions 67 3. Extracting Line Segments using Parametric Regression 67 4. Building a Polyhedron from Line Segments 68 5. Quantifying Polyhedron Attributes 71 E. EXPERT SYSTEM HEURISTICS FOR SONAR CLASSIFICATION . 74 1. Classification Heuristics and Attribute Heuristics 74 2. Pattern-match Classification Examples 76 3. Self-Diagnosis and Self-Correction 78 F. EXPERT SYSTEM PARADIGM 78 1. Expert System Characteristics 78 2. Knowledge Representation and Reasoning using Facts, Rules and an Inference Engine 79 3. Rule Sets and Control of Execution Flow 79 4. Developing an Expert System 80 G. IMPLEMENTATION AND EVALUATION 80 1. NPS AUV Vehicle Description and Sonar Characteristics 80 2. CLIPS Expert System 81 3. NPS AUV Sonar Classification System 83 4. NPS AUV Integrated Simulator 83 H. EXPERIMENTAL RESULTS 84 1. Classification Test Scenario 84 2. Experimental Results 84 I. DISCUSSIONS AND APPLICATIONS 86 1. Extendability to Video, Lasers, Complex Sonars and Sensor Fusion 86 2. Intelligent Remote Sensors 87 3. Data Reduction 88 4. Future Use of Expert Systems by Autonomous Vehicles 88 J. CONCLUSIONS 89 VII. SHORTEST PATH PLANNING USING A CIRCLE WORLD 90 A. ABSTRACT 90 B. INTRODUCTION AND PROBLEM DESCRIPTION OF CIRCLE WORLD 91 C. GEOMETRIC CHARACTERIZATIONS OF CIRCLE WORLD AND SHORTEST PATH 94 D. ALGORITHM FOR DETERMINING VISIBLE TANGENTS 102 E. SHORTEST-PATH DIJKSTRA AND A* SEARCH ALGORITHMS . 104 F. IMPLEMENTATION AND RESULTS 114 G. THREE-DIMENSIONAL APPLICATIONS