Published September 27, 2021
| Version 1
Journal article
Open
Towards an integrated automatic design process for robot swarms
Creators
- 1. IRIDIA, Université Libre de Bruxelles, Brussels, Belgium
Description
Background: The specification of missions to be accomplished by a robot swarm has been rarely discussed in the literature: designers do not follow any standardized processes or use any tool to precisely define a mission that must be accomplished.
Methods: In this paper, we introduce a fully integrated design process that starts with the specification of a mission to be accomplished and terminates with the deployment of the robots in the target environment. We introduce Swarm Mission Language (SML), a textual language that allows swarm designers to specify missions. Using model-driven engineering techniques, we define a process that automatically transforms a mission specified in SML into a configuration setup for an optimization-based design method. Upon completion, the output of the optimization-based design method is an instance of control software that is eventually deployed on real robots.
Results: We demonstrate the fully integrated process we propose on three different missions.
Conclusions: We aim to show that in order to create reliable, maintainable and verifiable robot swarms, swarm designers need to follow standardised automatic design processes that will facilitate the design of control software in all stages of the development.
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References
- Francesca G, Brambilla M, Brutschy A (2015). AutoMoDe-Chocolate: automatic design of control software for robot swarms. Swarm Intell. doi:10.1007/s11721-015-0107-9
- Dorigo M, Birattari M, Brambilla M (2014). Swarm robotics. Scholarpedia. doi:10.4249/scholarpedia.1463
- Bozhinoski D, Birattari M (2018). Designing control software for robot swarms: Software engineering for the development of automatic design methods.
- Brambilla M, Ferrante E, Birattari M (2013). Swarm robotics: a review from the swarm engineering perspective. Swarm Intell. doi:10.1007/s11721-012-0075-2
- Quinn M, Smith L, Mayley G (2003). Evolving controllers for a homogeneous system of physical robots: structured cooperation with minimal sensors. Philos Trans A Math Phys Eng Sci. doi:10.1098/rsta.2003.1258
- Trianni V (2008). Evolutionary swarm robotics: evolving self-organising behaviours in groups of autonomous robots. doi:10.1007/978-3-540-77612-3
- Francesca G, Brambilla M, Brutschy A (2014). AutoMoDe: a novel approach to the automatic design of control software for robot swarms. Swarm Intell. doi:10.1007/s11721-014-0092-4
- Birattari M, Ligot A, Hasselmann K (2020). Disentangling automatic and semi-automatic approaches to the optimization-based design of control software for robot swarms. Nat Mach Intell. doi:10.1038/s42256-020-0215-0
- Brugali D, Prassler E (2009). Software engineering for robotics. IEEE Robot Autom Mag. doi:10.1109/MRA.2009.932127
- Di Ruscio D, Malavolta I, Pelliccione P (2014). A family of domain-specific languages for specifying civilian missions of multi-robot systems.
- Bozhinoski D, Di Ruscio D, Malavolta I (2015). Flyaq: Enabling non-expert users to specify and generate missions of autonomous multicopters. doi:10.1109/ASE.2015.104
- Bozhinoski D, Garlan D, Malavolta I (2019). Managing safety and mission completion via collective run-time adaptation. J Syst Archit. doi:10.1016/j.sysarc.2019.02.018
- Hoos HH (2012). Programming by optimization. Commun ACM. doi:10.1145/2076450.2076469
- Francesca G, Birattari M (2016). Automatic design of robot swarms: achievements and challenges. Front Robot AI. doi:10.3389/frobt.2016.00029
- Birattari M, Ligot A, Bozhinoski D (2019). Automatic off-line design of robot swarms: a manifesto. Front Robot AI. doi:10.3389/frobt.2019.00059
- Schmidt DC (2006). Model-driven engineering. IEEE Computer.
- Schlegel C, Lotz A, Lutz M (2015). Model-driven software systems engineering in robotics: covering the complete life-cycle of a robot. Info Technol. doi:10.1515/itit-2014-1069
- Schlegel C, Haßler T, Lotz A (2009). Robotic software systems: From code-driven to model-driven designs.
- Hasselmann K, Ligot A, Ruddick J (2021). Empirical assessment and comparison of neuro-evolutionary methods for the automatic off-line design of robot swarms. Nat Commun. doi:10.1038/s41467-021-24642-3
- Pinciroli C, Trianni V, O'Grady R (2012). ARGoS: a modular, parallel, multi-engine simulator for multi-robot systems. Swarm Intell. doi:10.1007/s11721-012-0072-5
- Mondada F, Bonani M, Raemy X (2009). The e-puck, a robot designed for education in engineering.
- Nolfi S, Floreano D, Floreano DD (2000). Evolutionary robotics: The biology, intelligence, and technology of self-organizing machines.
- Nolfi S (2021). Behavioral and Cognitive Robotics: An Adaptive Perspective.
- Hauert S, Zufferey JC, Floreano D (2009). Reverse-engineering of artificially evolved controllers for swarms of robots. doi:10.1109/CEC.2009.4982930
- Ligot A, Birattari M (2020). Simulation-only experiments to mimic the effects of the reality gap in the automatic design of robot swarms. Swarm Intell. doi:10.1007/s11721-019-00175-w
- Koos S, Mouret JB, Doncieux S (2013). The transferability approach: crossing the reality gap in evolutionary robotics. IEEE Trans Evol Comput. doi:10.1109/TEVC.2012.2185849
- Haasdijk E, Bredeche N, Nolfi S (2014). Evolutionary robotics. Evol Intell. doi:10.1007/s12065-014-0113-7
- Birattari M, Ligot A, Francesca G (2021). AutoMoDe: a modular approach to the automatic off-line design and fine-tuning of control software for robot swarms. doi:10.1007/978-3-030-72069-8_5
- Geman S, Bienenstock E, Doursat R (1992). Neural networks and the bias/variance dilemma. Neural Comput.
- Birattari M, Stützle T, Paquete L (2002). A racing algorithm for configuring metaheuristics.
- Birattari M (2009). Tuning Metaheuristics: A Machine Learning Perspective.
- Birattari M, Yuan Z, Balaprakash P (2010). F-race and iterated f-race: An overview. doi:10.1007/978-3-642-02538-9_13
- Franzin A, Stützle T (2019). Revisiting simulated annealing: A component-based analysis. Comput Oper Res. doi:10.1016/j.cor.2018.12.015
- Hasselmann K, Birattari M (2020). Modular automatic design of collective behaviors for robots endowed with local communication capabilities. PeerJ Comput Sci. doi:10.7717/peerj-cs.291
- Ligot A, Kuckling J, Bozhinoski D (2020). Automatic modular design of robot swarms using behavior trees as a control architecture. PeerJ Comput Sci. doi:10.7717/peerj-cs.314
- Nordmann A, Hochgeschwender N, Wigand D (2016). A survey on domain-specific modeling and languages in robotics.
- Neill CJ, Laplante PA (2003). Requirements engineering: the state of the practice. IEEE Softw. doi:10.1109/MS.2003.1241365
- Van Lamsweerde A (2004). Goal-oriented requirements enginering: a roundtrip from research to practice. doi:10.1109/ICRE.2004.1335648
- Pinciroli C, Beltrame G (2016). Buzz: An extensible programming language for heterogeneous swarm robotics. doi:10.1109/IROS.2016.7759558
- Beltrame G, Merlo E, Panerati J (2018). Engineering safety in swarm robotics. doi:10.1145/3196558.3196565
- Brambilla M, Brutschy A, Dorigo M (2015). Property-driven design for swarm robotics: A design method based on prescriptive modeling and model checking. ACM Transactions on Autonomous and Adaptive Systems. doi:10.1145/2700318
- Kelly S, Tolvanen JP (2008). Domain-specific modeling: enabling full code generation. doi:10.1002/9780470249260
- Dixon C, Winfield AFT, Fisher M (2012). Towards temporal verification of swarm robotic systems. Rob Auton Syst. doi:10.1016/j.robot.2012.03.003
- Bonani M, Longchamp V, Magnenat S (2010). The marxbot, a miniature mobile robot opening new perspectives for the collective-robotic research. doi:10.1109/IROS.2010.5649153
- Riedo F, Chevalier M, Magnenat S (2013). Thymio II a robot that grows wiser with children. doi:10.1109/ARSO.2013.6705527
- Rubenstein M, Ahler C, Nagpal R (2012). Kilobot: A low cost scalable robot system for collective behaviors. doi:10.1109/ICRA.2012.6224638
- Soares JM, Navarro I, Martinoli A (2016). The Khepera IV mobile robot: performance evaluation, sensory data and software toolbox. doi:10.1007/2F978-3-319-27146-0_59
- Hasselmann K, Ligot A, Francesca G (2018). Reference models for AutoMoDe.
- Dwyer MB, Avrunin GS, Corbett JC (1999). Patterns in property specifications for finite-state verification. doi:10.1145/302405.302672
- Autili M, Grunske L, Lumpe M (2015). Aligning qualitative, real-time, and proba- bilistic property specification patterns using a structured english grammar. IEEE Trans Softw Eng. doi:10.1109/TSE.2015.2398877
- Eysholdt M, Behrens H (2010). Xtext: implement your language faster than the quick and dirty way. doi:10.1145/1869542.1869625
- Mondada F, Guignard A, Bonani M (2003). Swarm-bot: from concept to implementation. doi:10.1109/IROS.2003.1248877
- Bozhinoski D, Birattari M (2021). Integrated automatic design process for robot swarms.
- Garattoni L, Francesca G, Brutschy A (2015). Software infrastructure for e-puck (and TAM).
- Gutiérrez I, Campo A, Dorigo M (2009). Open e-puck range & bearing miniaturized board for local communication in swarm robotics. doi:10.1109/ROBOT.2009.5152456
- Bozhinoski D, Birattari M (2020). Requirements specification for swarm robotics: Supplementary material.