Evidence map›Paper›PMID 42664309›Full record

ArticlePloS one2026

Maximizing mobility: Distributed controllers of a Segway swarm for autonomous navigation in smart city environments.

Ronal Pranil Chand, Ravinesh Chand, Kritika Lal, Bibhya Sharma, Sandeep Ameet Kumar

Abstract read
In one paragraph

Article in PloS one, 2026. 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

5 authors.

Ronal Pranil ChandSchool of Mathematical & Computing Sciences, Fiji National University, Suva, Fiji.ORCID https://orcid.org/0000-0002-8527-040X
Ravinesh ChandSchool of Mathematical & Computing Sciences, Fiji National University, Suva, Fiji.
Kritika LalSchool of Information Technology, Engineering, Mathematics & Physics, The University of the South Pacific, Suva, Fiji.
Bibhya SharmaSchool of Information Technology, Engineering, Mathematics & Physics, The University of the South Pacific, Suva, Fiji.
Sandeep Ameet KumarSchool of Information Technology, Engineering, Mathematics & Physics, The University of the South Pacific, Suva, Fiji.ORCID https://orcid.org/0000-0002-6951-4742

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The advancement of autonomous multi-robot systems is critical for addressing the mobility challenges within modern smart city environments. Distributed, acceleration-based controllers are designed and mathematically validated for a Segway swarm navigating cluttered, time-varying urban settings. A Lyapunov-based Control Scheme (LbCS) is utilized to develop a potential function governing collective swarm behavior. This function ensures target convergence, enforces formation cohesion, and prevents inter-agent collisions. It also dictates safe navigation around static geometric constraints (modeled as disks and lines) and the evasion of independent dynamic obstacles. System stability is formally proven, demonstrating asymptotic controllability and convergence to the desired equilibrium state. Numerical simulations verify the framework's performance across four distinct scenarios, highlighting emergent reactive behaviors to moving entities. These results establish control strategies for the safe collective operation of non-holonomic robots, providing a theoretical foundation for future prototype development in smart city applications.

Indexed as

RoboticsAlgorithmsAutonomous RobotsCitiesComputer SimulationModels, Theoretical

Identifiers

PMID42664309
PMCPMC13524350

What OpenQuestion holds

Textmetadata
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.