Evidence map›Paper›PMID 34901173›Full record

ReviewFrontiers in robotics and AI2021

Morphological Computation in Plant Seeds for a New Generation of Self-Burial and Flying Soft Robots.

Barbara Mazzolai, Stefano Mariani, Marilena Ronzan, Luca Cecchini, Isabella Fiorello, Kliton Cikalleshi, Laura Margheri

Abstract readReview
In one paragraph

Review in Frontiers in robotics and AI, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. 4D Printing of Humidity-Driven Seed Inspired Soft Robots.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2023
    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

7 authors.

Barbara MazzolaiBioinspired Soft Robotics Laboratory, Istituto Italiano di Tecnologia, Genova, Italy.
Stefano MarianiBioinspired Soft Robotics Laboratory, Istituto Italiano di Tecnologia, Genova, Italy.
Marilena RonzanBioinspired Soft Robotics Laboratory, Istituto Italiano di Tecnologia, Genova, Italy.
Luca CecchiniBioinspired Soft Robotics Laboratory, Istituto Italiano di Tecnologia, Genova, Italy.
Isabella FiorelloBioinspired Soft Robotics Laboratory, Istituto Italiano di Tecnologia, Genova, Italy.
Kliton CikalleshiBioinspired Soft Robotics Laboratory, Istituto Italiano di Tecnologia, Genova, Italy.
Laura MargheriBioinspired Soft Robotics Laboratory, Istituto Italiano di Tecnologia, Genova, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Plants have evolved different mechanisms to disperse from parent plants and improve germination to sustain their survival. The study of seed dispersal mechanisms, with the related structural and functional characteristics, is an active research topic for ecology, plant diversity, climate change, as well as for its relevance for material science and engineering. The natural mechanisms of seed dispersal show a rich source of robust, highly adaptive, mass and energy efficient mechanisms for optimized passive flying, landing, crawling and drilling. The secret of seeds mobility is embodied in the structural features and anatomical characteristics of their tissues, which are designed to be selectively responsive to changes in the environmental conditions, and which make seeds one of the most fascinating examples of morphological computation in Nature. Particularly clever for their spatial mobility performance, are those seeds that use their morphology and structural characteristics to be carried by the wind and dispersed over great distances (i.e. "winged" and "parachute" seeds), and seeds able to move and penetrate in soil with a self-burial mechanism driven by their hygromorphic properties and morphological features. By looking at their motion mechanisms, new design principles can be extracted and used as inspiration for smart artificial systems endowed with embodied intelligence. This mini-review systematically collects, for the first time together, the morphological, structural, biomechanical and aerodynamic information from selected plant seeds relevant to take inspiration for engineering design of soft robots, and discusses potential future developments in the field across material science, plant biology, robotics and embodied intelligence.

Indexed as

bioinspired roboticsembodied intelligenceplant biologyplant biomechanicsseeds dispersalsmart materialssoft robotics

Identifiers

PMID34901173
PMCPMC8664382

What OpenQuestion holds

Textmetadata
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.