Engineering Swarms of Cyber-Physical Systems with the CPSwarm Workbench

Engineering swarms of cyber-physical systems (CPSs) is a complex process. We present the CPSwarm workbench that creates an automated design workflow to ease this process. This formalized workflow guides the user from modeling, to code generation, to deployment, both in simulation and on CPS hardware platforms. The workbench combines existing and emerging tools to solve real-world CPS swarm problems. As a proof-of-concept, we use the workbench to design a swarm of unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) for a search and rescue (SAR) use case. We evaluate the resulting swarm behaviors on three levels. First, abstract simulations for rapid prototyping. Second, detailed simulation to test the correctness of the results. Third, deployment on hardware to demonstrate the applicability. We measure the swarm performance in terms of area covered and victims rescued. The results show that the performance of the swarm is proportional to its size. Despite some manual steps, the proposed workbench shows to be well suited to ease the complicated task of deploying a swarm of CPSs.

[1]  Barbara Webb,et al.  Swarm Intelligence: From Natural to Artificial Systems , 2002, Connect. Sci..

[2]  Heinz Wörn,et al.  A framework of space–time continuous models for algorithm design in swarm robotics , 2008, Swarm Intelligence.

[3]  Lenka Pitonakova,et al.  Behaviour-data relations modelling language for multi-robot control algorithms , 2017, 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[4]  Edward A. Lee Cyber Physical Systems: Design Challenges , 2008, 2008 11th IEEE International Symposium on Object and Component-Oriented Real-Time Distributed Computing (ISORC).

[5]  M. Schranz,et al.  Modeling Swarm Intelligence Algorithms for CPS Swarms , 2020 .

[6]  Morgan Quigley,et al.  ROS: an open-source Robot Operating System , 2009, ICRA 2009.

[7]  C.J.H. Mann,et al.  A Practical Guide to SysML: The Systems Modeling Language , 2009 .

[8]  Flavio de Barros Vidal,et al.  A parallel hierarchical finite state machine approach to UAV control for search and rescue tasks , 2014, 2014 11th International Conference on Informatics in Control, Automation and Robotics (ICINCO).

[9]  Yuxin Zhao,et al.  Swarm intelligence: past, present and future , 2017, Soft Computing.

[10]  Paulo Tabuada,et al.  Pessoa 2.0: a controller synthesis tool for cyber-physical systems , 2011, HSCC '11.

[11]  Wilfried Elmenreich,et al.  Swarm Robotic Behaviors and Current Applications , 2020, Frontiers in Robotics and AI.

[12]  Hilding Elmqvist,et al.  Cyber-Physical Systems Modeling and Simulation with Modelica , 2011 .

[13]  Rodney A. Brooks,et al.  A Robust Layered Control Syste For A Mobile Robot , 2022 .

[14]  Aboul Ella Hassanien,et al.  Swarm Intelligence: Principles, Advances, and Applications , 2015 .

[15]  Alain Pirotte,et al.  Social Patterns for Designing Multiagent Systems , 2003, SEKE.

[16]  Mauro Birattari,et al.  Behavior Trees as a Control Architecture in the Automatic Modular Design of Robot Swarms , 2018, ANTS Conference.

[17]  KARL PEARSON,et al.  The Problem of the Random Walk , 1905, Nature.

[18]  Russ Abbott,et al.  Emergence explained: Abstractions: Getting epiphenomena to do real work , 2006, Complex..

[19]  Frank Vahid,et al.  A Survey on Concepts, Applications, and Challenges in Cyber-Physical Systems , 2014, KSII Trans. Internet Inf. Syst..

[20]  Camille Alain Rabbath A Finite-State Machine for Collaborative Airlift with a Formation of Unmanned Air Vehicles , 2013, J. Intell. Robotic Syst..

[21]  Wilfried Elmenreich,et al.  The CPSwarm Technology for Designing Swarms of Cyber-Physical Systems , 2019, STAF.

[22]  Sisay Adugna Chala,et al.  An Interactive Interface for Bulk Software Deployment in IoT , 2019, IOT.

[23]  Juha-Pekka Tolvanen,et al.  Domain-Specific Modeling: Enabling Full Code Generation , 2008 .

[24]  Wilfried Elmenreich,et al.  Modelling a CPS Swarm System: A Simple Case Study , 2018, MODELSWARD.

[25]  William Rand,et al.  An Introduction to Agent-Based Modeling: Modeling Natural, Social, and Engineered Complex Systems with NetLogo , 2015 .

[26]  Andre Gaschler,et al.  Robotics library: An object-oriented approach to robot applications , 2017, 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[27]  A. Cornils,et al.  Tool Support for Design Patterns based on Reference Attribute Grammars , 2000 .

[28]  Sandeep Neema,et al.  OpenMETA: A Model- and Component-Based Design Tool Chain for Cyber-Physical Systems , 2014, FPS@ETAPS.

[29]  William M. Spears,et al.  Evolving Finite-State Machine Strategies for Protecting Resources , 2000, ISMIS.

[30]  Jan Faigl,et al.  On benchmarking of frontier-based multi-robot exploration strategies , 2015, 2015 European Conference on Mobile Robots (ECMR).

[31]  Amnon H. Eden,et al.  Precise specification and automatic application of design patterns , 1997, Proceedings 12th IEEE International Conference Automated Software Engineering.

[32]  Sarah Mortimer,et al.  Road2CPS priorities and recommendations for research and innovation in cyber-physical systems , 2017 .

[33]  Erol Sahin,et al.  Probabilistic aggregation strategies in swarm robotic systems , 2005, Proceedings 2005 IEEE Swarm Intelligence Symposium, 2005. SIS 2005..

[34]  Edward A. Lee The Past, Present and Future of Cyber-Physical Systems: A Focus on Models , 2015, Sensors.

[35]  Mirko Viroli,et al.  Description and composition of bio-inspired design patterns: a complete overview , 2012, Natural Computing.

[36]  Dimitrios Kritharidis,et al.  ENOSYS FP7 EU project: An integrated modeling and synthesis flow for embedded systems design , 2012, 7th International Workshop on Reconfigurable and Communication-Centric Systems-on-Chip (ReCoSoC).

[37]  Peter Gorm Larsen,et al.  Co-modelling and co-simulation in the engineering of systems of cyber-physical systems , 2014, 2014 9th International Conference on System of Systems Engineering (SOSE).

[38]  Eliseo Ferrante,et al.  Swarm robotics: a review from the swarm engineering perspective , 2013, Swarm Intelligence.

[39]  Rafael S. Parpinelli,et al.  New inspirations in swarm intelligence: a survey , 2011, Int. J. Bio Inspired Comput..

[40]  Erol Sahin,et al.  Swarm Robotics: From Sources of Inspiration to Domains of Application , 2004, Swarm Robotics.

[41]  Rayleigh The Problem of the Random Walk , 1905, Nature.

[42]  Eliseo Ferrante,et al.  ARGoS: a modular, parallel, multi-engine simulator for multi-robot systems , 2012, Swarm Intelligence.

[43]  Mauro Birattari,et al.  AutoMoDe: A novel approach to the automatic design of control software for robot swarms , 2014, Swarm Intelligence.

[44]  Wilfried Elmenreich,et al.  Designing Swarms of Cyber-Physical Systems: the H2020 CPSwarm Project: Invited Paper , 2017, Conf. Computing Frontiers.

[45]  Edwin Olson,et al.  AprilTag 2: Efficient and robust fiducial detection , 2016, 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[46]  M. Schranz,et al.  Scalable Distributed Simulation for Evolutionary Optimization of Swarms of Cyber-Physical Systems , 2019 .

[47]  Petter Ögren,et al.  How Behavior Trees Modularize Hybrid Control Systems and Generalize Sequential Behavior Compositions, the Subsumption Architecture, and Decision Trees , 2017, IEEE Transactions on Robotics.

[48]  Jim Woodcock,et al.  Integrated tool chain for model-based design of Cyber-Physical Systems: The INTO-CPS project , 2016, 2016 2nd International Workshop on Modelling, Analysis, and Control of Complex CPS (CPS Data).

[49]  James D. McLurkin Stupid robot tricks : a behavior-based distributed algorithm library for programming swarms of robots , 2004 .

[50]  Paolo Fiorini,et al.  Search and Rescue Robotics , 2008, Springer Handbook of Robotics.

[51]  Edward A. Lee Fundamental Limits of Cyber-Physical Systems Modeling , 2016, ACM Trans. Cyber Phys. Syst..

[52]  Magnus Egerstedt,et al.  Hybrid systems tools for compiling controllers for cyber-physical systems , 2011, Discrete Event Dynamic Systems.

[53]  William Rand,et al.  Spectrum Modeling : From Simplicity to Elaboration and Realism in Urban Pattern Formation , 2007 .