Evidence map›Paper›PMID 41013089›Full record

ArticleSensors (Basel, Switzerland)2025

Fault Recovery Through Online Adaptation of Boolean Network Robots.

Paolo Baldini, Michele Braccini, Andrea Roli

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Paolo BaldiniDepartment of Computer Science and Engineering (DISI), Alma Mater Studiorum-Università di Bologna, Campus of Cesena, 47521 Cesena, Italy.ORCID 0000-0002-3625-5414
Michele BracciniDepartment of Computer Science and Engineering (DISI), Alma Mater Studiorum-Università di Bologna, Campus of Cesena, 47521 Cesena, Italy.ORCID 0000-0002-2335-2514
Andrea RoliDepartment of Computer Science and Engineering (DISI), Alma Mater Studiorum-Università di Bologna, Campus of Cesena, 47521 Cesena, Italy.ORCID 0000-0001-9891-5441

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Being able to recover from faults is a desired capability in robotics. This requires identifying ineffective behaviors and making some changes so as to display the desired one. In this work, we consider the problem of adjusting the controller of a robot so as to produce the desired behavior. Instead of considering complex and ad-hoc modifications, we leverage the automatic discovery of suitable solutions by means of online adaptation, a mechanism for the modification of the robot control strategy in runtime. Specifically, we use a performance function to identify ineffective behaviors and drive the controller design to an effective one. We also discuss the technical requirements for this procedure to succeed. The results suggest that online adaptation is suitable for the automatic recovery of functions after the occurrence of damages. Additionally, we show that adapting an existing controller to overcome a fault is faster than searching for a new controller from scratch.

Indexed as

Boolean Networksfault recoveryfault toleranceonline adaptationrobotics

Identifiers

PMID41013089
PMCPMC12473709

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.