Evidence map›Paper›PMID 41789151›Full record

ArticleInnovation (Cambridge (Mass.))2026

Magnetically controlled multimodal motion for environmentally adaptive soft millirobots with transformable wheel-leg morphology.

Shihao Zhong, Ruhao Nie, Zhiqiang Zheng, Yaozhen Hou, Qing Shi, Qiang Huang, Toshio Fukuda, Huaping Wang

Abstract read
In one paragraph

Article in Innovation (Cambridge (Mass.)), 2026. 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. A Bionic Multichannel Whisker System for Assisting Endoluminal Intervention.Cyborg and bionic systems (Washington, D.C.) · 2026
    Article
  3. Review
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

8 authors.

Shihao ZhongIntelligent Robotics Institute, School of Mechatronical Engineering, Beijing Institute of Technology, Beijing 100081, China.
Ruhao NieIntelligent Robotics Institute, School of Mechatronical Engineering, Beijing Institute of Technology, Beijing 100081, China.
Zhiqiang ZhengDepartment of Biomedical Engineering, City University of Hong Kong, Hong Kong SAR 999077, China.
Yaozhen HouIntelligent Robotics Institute, School of Mechatronical Engineering, Beijing Institute of Technology, Beijing 100081, China.
Qing ShiIntelligent Robotics Institute, School of Mechatronical Engineering, Beijing Institute of Technology, Beijing 100081, China.
Qiang HuangIntelligent Robotics Institute, School of Mechatronical Engineering, Beijing Institute of Technology, Beijing 100081, China.
Toshio FukudaDepartment of Micro-Nano Systems Engineering, Nagoya University, Furo-cho, Chikusa-ku, Nagoya, Aichi 464-8603, Japan.
Huaping WangIntelligent Robotics Institute, School of Mechatronical Engineering, Beijing Institute of Technology, Beijing 100081, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Small-scale soft robots with high morphological flexibility show significant potential for precise operation and sensing in confined environments. However, due to the coupled driving mechanism and the influence of environmental disturbances, the highly adaptable and stable navigation across diverse terrains through multimodal motion, which involves morphing shape and maintaining the reshaped configuration, still presents a major challenge for soft millirobots. Here, we develop a multi-stimuli-responsive millirobot with a multimodal locomotion adaptive control method, enhancing environmentally synergistic interactions and tasking capabilities. Constructed from materials responsive to temperature, humidity, and magnetic fields, the millirobot precisely navigates unstructured environments and independently controls deformation and locomotion. Theoretical models guide its polymorphic locomotion with optimal actuating parameters, such as bipedal walking in the two-leg mode and rolling in the wheel mode. A hierarchical dual-layer path-following controller manages path information and adjusts movement patterns. Experiments demonstrate the millirobot's environmental adaptability, morphological complementarity, and functional diversity. With various locomotion modes across different morphologies, the millirobot can traverse slopes, curved surfaces, stairs, slits, and gaps. It also performs tasks, such as cargo capture and transport, through morphological transformation. The proposed multimodal motion strategy based on polymorphism makes the soft millirobot a promising candidate for applications in micro-object manipulation and crevice inspection at confined, varied, and unstructured terrains.

Indexed as

environmentally adaptivemagnetic actuationmicrorobotmultimodal motionsoft robot

Identifiers

PMID41789151
PMCPMC12957565

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.