Property-Driven Design for Robot Swarms: A Design Method Based on Prescriptive Modeling and Model Checking

In this article, we present property-driven design, a novel top-down design method for robot swarms based on prescriptive modeling and model checking. Traditionally, robot swarms have been developed using a code-and-fix approach: in a bottom-up iterative process, the developer tests and improves the individual behaviors of the robots until the desired collective behavior is obtained. The code-and-fix approach is unstructured, and the quality of the obtained swarm depends completely on the expertise and ingenuity of the developer who has little scientific or technical support in his activity. Property-driven design aims at providing such scientific and technical support, with many advantages compared to the traditional unstructured approach. Property-driven design is composed of four phases: first, the developer formally specifies the requirements of the robot swarm by stating its desired properties; second, the developer creates a prescriptive model of the swarm and uses model checking to verify that this prescriptive model satisfies the desired properties; third, using the prescriptive model as a blueprint, the developer implements a simulated version of the desired robot swarm and validates the prescriptive model developed in the previous step; fourth, the developer implements the desired robot swarm and validates the previous steps. We demonstrate property-driven design using two case studies: aggregation and foraging.

[1]  Frank Ciesinski,et al.  On Probabilistic Computation Tree Logic , 2004, Validation of Stochastic Systems.

[2]  Marta Z. Kwiatkowska,et al.  Probabilistic symbolic model checking with PRISM: a hybrid approach , 2004, International Journal on Software Tools for Technology Transfer.

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

[4]  Marco Dorigo,et al.  Open E-puck Range & Bearing miniaturized board for local communication in swarm robotics , 2009, 2009 IEEE International Conference on Robotics and Automation.

[5]  DorigoMarco,et al.  Property-Driven Design for Robot Swarms , 2014 .

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

[7]  Christel Baier,et al.  Principles of model checking , 2008 .

[8]  Clare Dixon,et al.  Towards temporal verification of swarm robotic systems , 2012, Robotics Auton. Syst..

[9]  Clare Dixon,et al.  On Formal Specification of Emergent Behaviours in Swarm Robotic Systems , 2005 .

[10]  Nicholas R. Jennings,et al.  Pitfalls of agent-oriented development , 1998, AGENTS '98.

[11]  Christel Baier,et al.  Principles of Model Checking (Representation and Mind Series) , 2008 .

[12]  Richard F. Serfozo,et al.  Technical Note - An Equivalence Between Continuous and Discrete Time Markov Decision Processes , 1979, Oper. Res..

[13]  Heiko Hamann Towards swarm calculus: urn models of collective decisions and universal properties of swarm performance , 2013, Swarm Intelligence.

[14]  Jürgen Dix,et al.  Multi-Agent Programming , 2009, Springer US.

[15]  William M. Spears,et al.  Agent-Based Chemical Plume Tracing Using Fluid Dynamics , 2004, FAABS.

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

[17]  Mauro Birattari,et al.  The IRIDIA TAM: A device for task abstraction for the e-puck robot , 2010 .

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

[19]  Joaquin Miller,et al.  MDA Guide Version 1.0.1 , 2003 .

[20]  Vincent Nimal,et al.  Statistical Approaches for Probabilistic Model Checking , 2010 .

[21]  Diego Latella,et al.  On the use of Bio-PEPA for modelling and analysing collective behaviours in swarm robotics , 2013, Swarm Intelligence.

[22]  C. Mann,et al.  A Practical Treatise on Diseases of the Skin , 1889, Atlanta Medical and Surgical Journal (1884).

[23]  R. BurchJ.,et al.  Symbolic model checking , 1992 .

[24]  Spring Berman,et al.  Optimized Stochastic Policies for Task Allocation in Swarms of Robots , 2009, IEEE Transactions on Robotics.

[25]  Mauro Birattari,et al.  Swarm Intelligence , 2012, Lecture Notes in Computer Science.

[26]  Sérgio Vale Aguiar Campos,et al.  Symbolic Model Checking , 1993, CAV.

[27]  S. Jørgensen Models in Ecology , 1975 .

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

[29]  M. Wooldridge,et al.  Organisational Abstractions for the Analysis and Design of Multi-Agent Systems , 2000 .

[30]  Wolfgang Banzhaf,et al.  Why complex systems engineering needs biological development , 2007, Complex..

[31]  J. Deneubourg,et al.  Self-organized aggregation in cockroaches , 2005, Animal Behaviour.

[32]  Mauro Birattari,et al.  An Experiment in Automatic Design of Robot Swarms - AutoMoDe-Vanilla, EvoStick, and Human Experts , 2014, ANTS Conference.

[33]  Kent L. Beck,et al.  Test-driven Development - by example , 2002, The Addison-Wesley signature series.

[34]  Francesco Mondada,et al.  The e-puck, a Robot Designed for Education in Engineering , 2009 .

[35]  Mauro Birattari,et al.  Interference Reduction through Task Partitioning in a Robotic Swarm - Or: "Don't you Step on My Blue Suede Shoes!" , 2009, ICINCO-RA.

[36]  S. Kazadi,et al.  Model independence in swarm robotics , 2009, Int. J. Intell. Comput. Cybern..

[37]  Clare Dixon,et al.  Analysing robot swarm behaviour via probabilistic model checking , 2012, Robotics Auton. Syst..

[38]  LermanKristina,et al.  Mathematical Model of Foraging in a Group of Robots , 2002 .

[39]  Mauro Birattari,et al.  Property-driven design for swarm robotics , 2012, AAMAS.

[40]  Kristina Lerman,et al.  Mathematical Model of Foraging in a Group of Robots: Effect of Interference , 2002, Auton. Robots.

[41]  Dani Goldberg Design and Evaluation of Robust Behavior-Based Controllers for Distributed Multi-Robot Collection Tasks , 2001 .

[42]  Bengt Jonsson,et al.  A logic for reasoning about time and reliability , 1990, Formal Aspects of Computing.

[43]  R. Serfozo An Equivalence between Continuous and Discrete Time Markov Decision Processes. , 1976 .

[44]  Amanda J. C. Sharkey,et al.  Swarm robotics , 2014, Scholarpedia.

[45]  Jürgen Dix,et al.  Multi-Agent Programming: Languages, Tools and Applications , 2009 .

[46]  Spring Berman,et al.  Design of control policies for spatially inhomogeneous robot swarms with application to commercial pollination , 2011, 2011 IEEE International Conference on Robotics and Automation.

[47]  Kristina Lerman,et al.  A Review of Probabilistic Macroscopic Models for Swarm Robotic Systems , 2004, Swarm Robotics.