Evidence map›Paper›PMID 40018342›Full record

ReviewFrontiers in robotics and AI2025

Grand challenges for burrowing soft robots.

Caitlin L Le, Osman Dogan Yirmibesoglu, Sean Even, Trevor Buckner, Yasemin Ozkan-Aydin, Rebecca Kramer-Bottiglio

Abstract readReview
In one paragraph

Review in Frontiers in robotics and AI, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

6 authors.

Caitlin L Le *Department of Mechanical Engineering and Materials Science, Yale University, New Haven, CT, United States.
Osman Dogan Yirmibesoglu *Department of Mechanical Engineering and Materials Science, Yale University, New Haven, CT, United States.
Sean EvenDepartment of Electrical Engineering, University of Notre Dame, Notre Dame, IN, United States.
Trevor BucknerDepartment of Mechanical Engineering and Materials Science, Yale University, New Haven, CT, United States.
Yasemin Ozkan-AydinDepartment of Electrical Engineering, University of Notre Dame, Notre Dame, IN, United States.
Rebecca Kramer-BottiglioDepartment of Mechanical Engineering and Materials Science, Yale University, New Haven, CT, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Robotic burrowing holds promise for applications in agriculture, resource extraction, and infrastructure development, but current approaches are ineffective, inefficient, or cause significant environmental disruption. In contrast, natural burrowers penetrate substrates with minimal disturbance, providing biomechanical principles that could inspire more efficient and sustainable mechanisms. A notable feature of many natural burrowers is their reliance on soft body compositions, raising the question of whether softness contributes to their burrowing success. This review explores the role of soft materials in biological burrowing and their implications for robotic design. We examine the mechanisms that soft-bodied organisms and soft robots employ for submerging and subterranean locomotion, focusing on how softness enhances efficiency and adaptability in granular media. We analyze the gaps between the capabilities of natural burrowers and soft robotic burrowers, identify grand challenges, and propose opportunities to enhance robotic burrowing performance. By bridging biological principles with engineering innovation, this review aims to inform the development of next-generation burrowing robots capable of operating with the efficiency and efficacy seen in nature.

Indexed as

bioinspirationburrowinggranular mediasoft roboticssoil

Identifiers

PMID40018342
PMCPMC11864953

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.