Integrated simulation environment for unmanned autonomous systems: towards a conceptual framework

The paper initiates a comprehensive conceptual framework for an integrated simulation environment for unmanned autonomous systems (UAS) that is capable of supporting the design, analysis, testing, and evaluation from a "system of systems" perspective. The paper also investigates the current state of the art of modeling and performance assessment of UAS and their components and identifies directions for future developments. All the components of a comprehensive simulation environment focused on the testing and evaluation of UAS are identified and defined through detailed analysis of current and future required capabilities and performance. The generality and completeness of the simulation environment is ensured by including all operational domains, types of agents, external systems, missions, and interactions between components. The conceptual framework for the simulation environment is formulated with flexibility, modularity, generality, and portability as key objectives. The development of the conceptual framework for the UAS simulation reveals important aspects related to the mechanisms and interactions that determine specific UAS characteristics including complexity, adaptability, synergy, and high impact of artificial and human intelligence on system performance and effectiveness.

[1]  Lawrence Chung,et al.  Process-Oriented Metrics for Software Architecture Adaptability , 2001, Proceedings Fifth IEEE International Symposium on Requirements Engineering.

[2]  Brian Goldiez,et al.  A Survey of Commercial & Open Source Unmanned Vehicle Simulators , 2007, Proceedings 2007 IEEE International Conference on Robotics and Automation.

[3]  H. Shim,et al.  A comprehensive study of control design for an autonomous helicopter , 1998, Proceedings of the 37th IEEE Conference on Decision and Control (Cat. No.98CH36171).

[4]  Yacov Y. Haimes,et al.  Risk modeling, assessment, and management , 1998 .

[5]  Rodney E. Schultz,et al.  Simulation modeling for military logistics and supportability studies , 1991, 1991 Winter Simulation Conference Proceedings..

[6]  Duncan A. Campbell,et al.  An intelligent control architecture for unmanned aerial systems (UAS) in the National Airspace System (NAS) , 2007 .

[7]  Andrew Cox,et al.  Systems Approach to Unmanned Air Vehicle Development and Certification , 2008, SSS.

[8]  Irene M. Gregory,et al.  General Equations of Motion for a Damaged Asymmetric Aircraft , 2007 .

[9]  S. Shankar Sastry,et al.  Generation of conflict resolution manoeuvres for air traffic management , 1997, Proceedings of the 1997 IEEE/RSJ International Conference on Intelligent Robot and Systems. Innovative Robotics for Real-World Applications. IROS '97.

[10]  James Albus 4D/RCS: A Reference Model Architecture for Unmanned Vehicle Systems , 2002 .

[11]  John Keller Human performance modeling for discrete-event simulation: human performance modeling for discrete-ev , 2002 .

[12]  Subbarao Kambhampati,et al.  Hierarchical Strategy Learning with Hybrid Representations , 2007, AAAI 2007.

[13]  Carl D. Crane,et al.  Perception and Planning Architecture for Autonomous Ground Vehicles , 2006, Computer.

[14]  Jacques Durand,et al.  Mass-transit system service quality: tradeoff analysis on reliability, maintainability and logistics , 1995, Annual Reliability and Maintainability Symposium 1995 Proceedings.

[15]  Devendra P. Garg,et al.  Sensor Modeling and Multi-Sensor Data Fusion , 2005 .

[16]  Sai-Ming Li,et al.  On-line failure detection and identification (FDI) and adaptive reconfigurable control (ARC) in aerospace applications , 2001, Proceedings of the 2001 American Control Conference. (Cat. No.01CH37148).

[17]  R. John Hansman,et al.  An Integrated Approach to Evaluating Risk Mitigation Measures for UAV Operational Concepts in the NAS , 2005 .

[18]  Raja Parasuraman,et al.  Effects of Automated Conflict Cuing and Traffic Density on Air Traffic Controller Performance and Visual Attention in a Datalink Environment , 2006 .

[19]  Jens Rasmussen,et al.  Models of Mental Strategies in Process Plant Diagnosis , 1981 .

[20]  John Keller,et al.  Human performance modeling for discrete-event simulation: workload , 2002, Proceedings of the Winter Simulation Conference.

[21]  Scott A. Bortoff,et al.  Path planning for UAVs , 2000, Proceedings of the 2000 American Control Conference. ACC (IEEE Cat. No.00CH36334).

[22]  G. G. Stokes "J." , 1890, The New Yale Book of Quotations.

[23]  Carl D. Crane,et al.  Planning and modeling extensions to the Joint Architecture for Unmanned Systems (JAUS) for application to unmanned ground vehicles , 2005, SPIE Defense + Commercial Sensing.

[24]  Mario G. Perhinschi,et al.  Modelling and Simulation of a Fault-Tolerant Flight Control System , 2006 .

[25]  Kevin Wise Guidance and Control for Military Systems: Future Challenges , 2007 .

[26]  Francesca De Crescenzio,et al.  Advanced interface for UAV (Unmanned Aerial Vehicle) Ground Control Station , 2007 .

[27]  Alexander Leonessa,et al.  Design of a small, multi-purpose, autonomous surface vessel , 2003, Oceans 2003. Celebrating the Past ... Teaming Toward the Future (IEEE Cat. No.03CH37492).

[28]  J. Crandall,et al.  Using Discrete-Event Simulation to Model Situational Awareness of Unmanned-Vehicle Operators , 2008 .

[29]  Lockheed Martin,et al.  Enabling Cognitive Architectures for UAV Mission Planning , 2006 .

[30]  Scott A. DeLoach,et al.  Using Design Metrics for Predicting System Flexibility , 2006, FASE.

[31]  Trey Smith,et al.  TECHNOLOGY FOR AUTONOMOUS SPACE SYSTEMS , 2002 .

[32]  Alonzo Kelly,et al.  Toward Reliable Off Road Autonomous Vehicles Operating in Challenging Environments , 2006, Int. J. Robotics Res..

[33]  James S. Albus,et al.  Metrics and Performance Measures for Intelligent Unmanned Ground Vehicles , 2002 .

[34]  Peter H. Zipfel Modeling and Simulation of Aerospace Vehicle Dynamics (Aiaa Education) , 2003 .

[35]  James K. Kuchar,et al.  A review of conflict detection and resolution modeling methods , 2000, IEEE Trans. Intell. Transp. Syst..

[36]  Aaas News,et al.  Book Reviews , 1893, Buffalo Medical and Surgical Journal.

[37]  Mark E. Dreier Introduction to Helicopter and Tiltrotor Simulation , 2007 .

[38]  Santiago Ontañón,et al.  An Ensemble Learning and Problem Solving Architecture for Airspace Management , 2009, IAAI.

[39]  Seng Cheong Telly Poh Simulations of Diversity Techniques for Urban UAV Data Links , 2004 .

[40]  Mark L. Hanson,et al.  An Intelligent Agent for Supervisory Control of Teams of Unihabited Combat Air Vehicles (UCAVs) , 2000 .

[41]  Joseph F. Horn,et al.  A Simulation Test Bed for Coordination of Unmanned Rotorcraft and Ground Vehicles , 2006 .

[42]  N Navet CONTROLLER AREA NETWORK , 1998 .

[43]  Peter Weinstein,et al.  Towards a Complete, Multi-level Cognitive Architecture , 2007 .

[44]  Joe Twesme,et al.  NAVAL AIR SYSTEMS COMMAND (NAVAIR) UNMANNED AERIAL VEHICLE (UAV) / UNMANNED COMBAT AERIAL VEHICLE (UCAV) DISTRIBUTED SIMULATION INFRASTRUCTURE * , 2003 .

[45]  Mario G. Perhinschi,et al.  A Simulation Environment for Testing and Research of Neurally Augmented Fault Tolerant Control Laws Based on Non-Linear Dynamic Inversion , 2004 .

[46]  E. Analysis of Logistic Supportability for Complex Systems , .

[47]  Washington Y. Ochieng,et al.  Performance Evaluation of a Novel 4D Trajectory Prediction Model for Civil Aircraft , 2008, Journal of Navigation.

[48]  Eric R. Mueller,et al.  Hardware -in -the -loop Simulation Design for Evaluation of Unmanned Aerial Vehicle Control Systems , 2007 .

[49]  Carl D. Crane,et al.  An adaptive planning framework for situation assessment and decision-making on an autonomous ground vehicle , 2006 .

[50]  Nidal Jodeh,et al.  Development of Small Unmanned Aerial Vehicle Research Platform: Modeling and Simulating with Flight Test Validation , 2006 .

[51]  William Lucyshyn,et al.  Evaluation of Performance Based Logistics , 2006 .

[52]  Simon Newman Introduction to helicopter and tiltrotor flight simulation , 2007 .

[53]  Liang Tang,et al.  From mission planning to flight control of unmanned aerial vehicles: Strategies and implementation tools , 2005, Annu. Rev. Control..

[54]  Gaurav S. Sukhatme,et al.  Heterogeneous Robot Group Control and Applications , 1999 .

[55]  M. DeGarmo Issues Concerning Integration of Unmanned Aerial Vehicles in Civil Airspace November 2004 , 2004 .

[56]  J. Adams Unmanned Vehicle Situation Awareness : A Path Forward , 2007 .

[57]  Peter Drewes Cole,et al.  Simulation based Approach for Unmanned System Command and Control , 2006 .

[58]  Octavian Paul Rotaru,et al.  Reusability metrics for software components , 2005, The 3rd ACS/IEEE International Conference onComputer Systems and Applications, 2005..

[59]  W. Marsden I and J , 2012 .

[60]  Michael Lichtsinder,et al.  Jet Engine Model for Control and Real-Time Simulations , 2006 .

[61]  Ernest H. Page,et al.  Introduction to military training simulation: a guide for discrete event simulationists , 1998, 1998 Winter Simulation Conference. Proceedings (Cat. No.98CH36274).

[62]  I Pritchard Jocelyn An Overview of Landing Gear Dynamics , 1999 .

[63]  D. E. Peercy A software maintainability evaluation methodology , 1979 .

[64]  Phillip R. Chandler,et al.  MultiUAV: a multiple UAV simulation for investigation of cooperative control , 2002, Proceedings of the Winter Simulation Conference.

[65]  P ? ? ? ? ? ? ? % ? ? ? ? , 1991 .

[66]  César Muñoz,et al.  Conflict Detection and Resolution for 1,2,...N Aircraft , 2007 .

[67]  Peter H. Zipfel,et al.  Modeling and Simulation of Aerospace Vehicle Dynamics, Second Edition , 2007 .

[68]  R. Sharma,et al.  Swarm Intelligence based Collision Avoidance Between Realistically Modelled UAV Clusters , 2007, 2007 American Control Conference.

[69]  Marc L. Steinberg,et al.  Comparison of Intelligent, Adaptive, and Nonlinear Flight Control Laws , 1999 .

[70]  M. Pachter,et al.  Challenges of autonomous control , 1998 .

[71]  M. Steinberg,et al.  Metrics for Intelligent Autonomy , 2004 .

[72]  Charles R. Allen,et al.  Wireless communication between AGVs (autonomous guided vehicles) and the industrial network CAN (controller area network) , 2002, Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292).

[73]  C. Dimou,et al.  Towards a Generic Methodology for Evaluating MAS Performance , 2007, 2007 International Conference on Integration of Knowledge Intensive Multi-Agent Systems.

[74]  Charles Patchett,et al.  A Preliminary Model of Accident Causality for Uninhabited Autonomous Air Systems and Its Implications for Their Decision Architectures , 2008, Tenth International Conference on Computer Modeling and Simulation (uksim 2008).

[75]  D. E. Mortin Analysis of logistic supportability for complex systems (military communications) , 1990, Annual Proceedings on Reliability and Maintainability Symposium.

[76]  Jean Scholtz,et al.  Common metrics for human-robot interaction , 2006, HRI '06.

[77]  Reece A. Clothier,et al.  A Casualty Risk Analysis For Unmanned Aerial System (UAS) Operations Over Inhabited Areas , 2007 .

[78]  Ronald C. Arkin,et al.  Multiagent Mission Specification and Execution , 1997, Auton. Robots.

[79]  Elena R. Messina,et al.  A Framework For Autonomy Levels For Unmanned Systems (ALFUS) , 2005 .

[80]  Hui-Min Huang,et al.  Terminology for Specifying the Autonomy Levels for Unmanned Systems: Version 1.0 , 2004 .