Automatic Design of Communication-Based Behaviors for Robot Swarms

Hasselmann, Ken; Robert, Frédéric; Birattari, Mauro

doi:10.1007/978-3-030-00533-7_2

Cited by 28 publications

(34 citation statements)

References 44 publications

(60 reference statements)

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“…The two methods-AutoMoDe-Vanilla and AutoMoDe-Chocolate-have shown to produce control software that crosses the reality gap more satisfactorily than those produced by EvoStick, an implementation of the traditional neuro-evolutionary robotics (Francesca et al 2014(Francesca et al , 2015. These results were further confirmed by follow up studies (Kuckling et al 2018;Hasselmann et al 2018b).…”

Section: Focus On Simulation Models To Reduce Differences Between Simmentioning

confidence: 77%

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Simulation-only experiments to mimic the effects of the reality gap in the automatic design of robot swarms

Ligot

Birattari

2019

Swarm Intell

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The reality gap-the discrepancy between reality and simulationis a critical issue in the off-line automatic design of control software for robot swarms, as well as for single robots. It is understood that the reality gap manifests itself as a drop in performance: when control software generated in simulation is ported to physical robots, the performance observed is often disappointing compared with the one obtained in simulation. In this paper, we investigate whether, to observe the effects of the reality gap, it is necessary to assume that the control software is designed in a context that is simpler than the one in which it is evaluated. In a first experiment, we show that a performance drop may be observed also in an artificial, simulation-only reality gap: control software is generated on the basis of a simulation model and assessed on a second one. We will call this second model a pseudo-reality. We selected the simulation model to be used as a pseudo-reality by trial and error, so as to qualitatively replicate previously published observations made in experiments with physical robots. The results show that a performance drop occurs even if we can exclude that pseudo-reality is more complex than the simulation model used for the design. In a second experiment, we eliminate the trial-and-error selection of the first experiment by evaluating control software across multiple pseudo-realities, which are sampled around the original simulation model used for the design. The results of the second experiment confirm those of the first one and show that they do not depend on the specific pseudo-reality we previously selected by trial and error. Moreover, they suggest that one could use multiple pseudo-realities to evaluate automatic design methods and, from this simulation-only evaluation, infer their robustness to the reality gap. The experiments were conceived by the two authors and performed by AL. The article was drafted by AL and revised by the two authors. The research was directed by MB.

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Section: Focus On Simulation Models To Reduce Differences Between Simmentioning

confidence: 77%

“…These variables are updated at every control cycle (that is, every 100 ms). A formal definition of the sensors and actuators, and the corresponding variables is given by the reference model RM 1.1 (Hasselmann et al 2018a) of Table 2.…”

Section: Simulated Robotsmentioning

confidence: 99%

Simulation-only experiments to mimic the effects of the reality gap in the automatic design of robot swarms

Ligot

Birattari

2019

Swarm Intell

Self Cite

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“…Minimal instances of communications have also been evolved to allow the synchronization of a swarm (Trianni and Nolfi, 2009), as well as to coordinate the activities in robot pairs (Tuci, 2009;De Greeff and Nolfi, 2010;Uno et al, 2011). Besides evolutionary approaches, other automatic design methods have been proposed that are capable of producing efficient communication for behaviors such as aggregation, coordination, and categorization (Hasselmann et al, 2018). By looking at these and similar research studies not mentioned here for brevity, some important lessons can be learned.…”

Section: First Steps In the Evolution Of Communicationmentioning

confidence: 99%

Language Evolution in Swarm Robotics: A Perspective

et al. 2020

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While direct local communication is very important for the organization of robot swarms, so far it has mostly been used for relatively simple tasks such as signaling robots preferences or states. Inspired by the emergence of meaning found in natural languages, more complex communication skills could allow robot swarms to tackle novel situations in ways that may not be a priori obvious to the experimenter. This would pave the way for the design of robot swarms with higher autonomy and adaptivity. The state of the art regarding the emergence of communication for robot swarms has mostly focused on offline evolutionary approaches, which showed that signaling and communication can emerge spontaneously even when not explicitly promoted. However, these approaches do not lead to complex, language-like communication skills, and signals are tightly linked to environmental and/or sensory-motor states that are specific to the task for which communication was evolved. To move beyond current practice, we advocate an approach to emergent communication in robot swarms based on language games. Thanks to language games, previous studies showed that cultural self-organization-rather than biological evolution-can be responsible for the complexity and expressive power of language. We suggest that swarm robotics can be an ideal test-bed to advance research on the emergence of language-like communication. The latter can be key to provide robot swarms with additional skills to support self-organization and adaptivity, enabling the design of more complex collective behaviors.

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“…Chocolate (Francesca et al, 2015), Gianduja (Hasselmann et al, 2018b), and Maple (Kuckling et al, 2018). Each of these methods is characterized by a specific set of predefined modules, a software architecture into which these modules can be combined, and an optimization algorithm that searches the space of the possible ways in which modules can be combined into the given architecture and the space of the free parameters.…”

Section: Automode-wafflementioning

confidence: 99%

“…In this research, we introduce Waffle, a new instance of the AutoMoDe family of automatic design methods. All previously published instances of AutoMoDe generate control software for the e-puck platform (Mondada et al, 2009) by selecting, combining, and fine-tuning predefined, mission-independent software modules (Francesca et al, 2014(Francesca et al, , 2015Kuckling et al, 2018;Hasselmann et al, 2018b). Waffle is based on Chocolate (Francesca et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Peer Review #1 of "Concurrent design of control software and configuration of hardware for robot swarms under economic constraints (v0.1)"

2019

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Designing a robot swarm is challenging due to its self-organized and distributed nature: complex relations exist between the behavior of the individual robots and the collective behavior that results from their interactions. In this paper, we study the concurrent automatic design of control software and the automatic configuration of the hardware of robot swarms. We introduce Waffle, a new instance of the AutoMoDe family of automatic design methods that produces control software in the form of a probabilistic finite state machine, configures the robot hardware, and selects the number of robots in the swarm. We test Waffle under economic constraints on the total monetary budget available and on the battery capacity of each individual robot comprised in the swarm. Experimental results obtained via realistic computer-based simulation on three collective missions indicate that different missions require different hardware and software configuration, and that Waffle is able to produce effective and meaningful solutions under all the experimental conditions considered.

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Automatic Design of Communication-Based Behaviors for Robot Swarms

Cited by 28 publications

References 44 publications

Simulation-only experiments to mimic the effects of the reality gap in the automatic design of robot swarms

Simulation-only experiments to mimic the effects of the reality gap in the automatic design of robot swarms

Language Evolution in Swarm Robotics: A Perspective

Peer Review #1 of "Concurrent design of control software and configuration of hardware for robot swarms under economic constraints (v0.1)"

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