Evidence map›Paper›PMID 19557691›Full record

ArticleThe International journal of developmental biology2009

Regenerative patterning in Swarm Robots: mutual benefits of research in robotics and stem cell biology.

Michael Rubenstein, Ying Sai, Cheng-Ming Chuong, Wei-Min Shen

Abstract read
In one paragraph

Article in The International journal of developmental biology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Review
  2. Review
  3. Deciphering principles of morphogenesis from temporal and spatial patterns on the integument.Developmental dynamics : an official publication of the American Association of Anatomists · 2015
    Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. Pattern formation today.The International journal of developmental biology · 2009
    Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Michael RubensteinInformation Sciences Institute and Computer Science Department, University of Southern California, 90292, USA.
Ying Sai
Cheng-Ming Chuong
Wei-Min Shen

Funding

Size regulation of skin appendagesR01AR047364 · NIAMS · UNIVERSITY OF SOUTHERN CALIFORNIA · PI Cheng-Ming Chuong · 2002 to 2026
$10.1M
LIW5R01AR042177 · NIAMS · UNIVERSITY OF SOUTHERN CALIFORNIA · PI CHUONG, CHENG-MING · 1995 to 2013
$5.7M
Repair and regeneration in a novel animal modelR03AG027932 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI CHUONG, CHENG-MING · 2007 to 2008
$132k
NIAMS NIH HHS R01 AR042177NIAMS NIH HHS R01 AR047364NIA NIH HHS R03 AG027932
6 · The paper itself

Abstract

This paper presents a novel perspective of Robotic Stem Cells (RSCs), defined as the basic non-biological elements with stem cell like properties that can self-reorganize to repair damage to their swarming organization. Self here means that the elements can autonomously decide and execute their actions without requiring any preset triggers, commands, or help from external sources. We develop this concept for two purposes. One is to develop a new theory for self-organization and self-assembly of multi-robots systems that can detect and recover from unforeseen errors or attacks. This self-healing and self-regeneration is used to minimize the compromise of overall function for the robot team. The other is to decipher the basic algorithms of regenerative behaviors in multi-cellular animal models, so that we can understand the fundamental principles used in the regeneration of biological systems. RSCs are envisioned to be basic building elements for future systems that are capable of self-organization, self-assembly, self-healing and self-regeneration. We first discuss the essential features of biological stem cells for such a purpose, and then propose the functional requirements of robotic stem cells with properties equivalent to gene controller, program selector and executor. We show that RSCs are a novel robotic model for scalable self-organization and self-healing in computer simulations and physical implementation. As our understanding of stem cells advances, we expect that future robots will be more versatile, resilient and complex, and such new robotic systems may also demand and inspire new knowledge from stem cell biology and related fields, such as artificial intelligence and tissue engineering.

Indexed as

AlgorithmsAnimalsArtificial IntelligenceCell DifferentiationCell ProliferationComputer SimulationDevelopmental BiologyHematopoietic Stem CellsHumansModels, BiologicalProgramming LanguagesRegenerationRoboticsSoftwareTissue Engineering

Identifiers

PMID19557691
PMCPMC2874133

What OpenQuestion holds

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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.