Evidence map›Paper›PMID 33500973›Full record

ReviewFrontiers in robotics and AI2018

Toward Formal Models and Languages for Verifiable Multi-Robot Systems.

Rocco De Nicola, Luca Di Stefano, Omar Inverso

Abstract readReview
In one paragraph

Review in Frontiers in robotics and AI, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Rocco De NicolaIMT School for Advanced Studies, Lucca, Italy.
Luca Di StefanoGran Sasso Science Institute, L'Aquila, Italy.
Omar InversoGran Sasso Science Institute, L'Aquila, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Incorrect operation of a multi-robot system (MRS) may not only lead to unsatisfactory results, but it can also cause economic losses and jeopardize safety. These risks may not always be evident, since they may arise as unforeseen consequences of interactions between different components of the system. Thus, tools and techniques that can help in providing guarantees about the behavior of MRSs are on demand; whenever possible, these guarantees should be backed up by formal proofs complementing the traditional approaches based on testing and simulation. Tailored linguistic support to specify MRSs is a major step toward this goal. In fact, reducing the gap between typical features of an MRS and the linguistic primitives used to model them would simplify both the specification of these systems and their verification. With the aim of reducing this gap, we identified some key features of MRSs in this work. Subsequently, we considered the selection of three specification languages oriented toward MRSs, which are representative of wider categories of languages with similar aims. Finally, we assessed the extent to which the considered languages captured the key features in an adequate and intuitive way by using them to implement multi-robot systems case studies.

Indexed as

automated reasoningcollective behaviorcommunicationlanguagesmulti-robot systems

Identifiers

PMID33500973
PMCPMC7806004

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.