Evidence map›Paper›PMID 41044094›Full record

ArticleNature communications2025

AI-embodied multi-modal flexible electronic robots with programmable sensing, actuating and self-learning.

Junfeng Li, Zhangyu Xu, Nanpei Li, Kaijun Zhang, Guangyong Xiong, Minjie Sun, Chao Hou, Jingjing Ji, Fan Zhang, Junwen Zhong and 1 more

Abstract read
In one paragraph

Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
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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

11 authors.

Junfeng LiSchool of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan, China.ORCID http://orcid.org/0000-0001-6095-295X
Zhangyu XuState Key Laboratory of Intelligent Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, China.
Nanpei LiSchool of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan, China.
Kaijun ZhangDepartment of Electromechanical Engineering, Centre for Artificial Intelligence and Robotics, University of Macau, Macau, China.ORCID http://orcid.org/0000-0002-9924-2928
Guangyong XiongSchool of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan, China.
Minjie SunSchool of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan, China.
Chao HouState Key Laboratory of Intelligent Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, China.
Jingjing JiState Key Laboratory of Intelligent Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, China.
Fan ZhangState Key Laboratory of Intelligent Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, China. fanzhang@hust.edu.cn.ORCID http://orcid.org/0000-0002-3658-9887
Junwen ZhongDepartment of Electromechanical Engineering, Centre for Artificial Intelligence and Robotics, University of Macau, Macau, China. junwenzhong@um.edu.mo.ORCID http://orcid.org/0000-0002-0232-1604
YongAn HuangState Key Laboratory of Intelligent Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, China. yahuang@hust.edu.cn.ORCID http://orcid.org/0000-0001-7713-8380

Funding

Fundo para o Desenvolvimento das Ciências e da Tecnologia (Science and Technology Development Fund) 0117/2024/AMJNational Natural Science Foundation of China (National Science Foundation of China) 52188102National Natural Science Foundation of China (National Science Foundation of China) 52525502
6 · The paper itself

Abstract

Achieving robust environmental interaction in small-scale soft robotics remains challenging due to limitations in terrain adaptability, real-time perception, and autonomous decision-making. Here, we introduce Flexible Electronic Robots constructed from programmable flexible electronic components and setae modules. The integrated platform combines multimodal sensing/actuation with embedded computing, enabling adaptive operation in diverse environments. Applying modular design principles to configure structural topologies, actuation sequences, and circuit layouts, these robots achieve multimodal locomotion, including vertical surface traversal, directional control, and obstacle navigation. The system implements proprioception (shape and attitude) and exteroception (vision, temperature, humidity, proximity and pathway shape recognition) under dynamic conditions. Onboard computational units enable autonomous behaviors like hazard evasion and thermal gradient tracking through adaptive decision-making, supported by embodied artificial intelligence. In this work, we establish a framework for creating small-scale soft robots with enhanced environmental intelligence through tightly integrated sensing, actuation, and decision-making architectures.

Identifiers

PMID41044094
PMCPMC12494961

What OpenQuestion holds

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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.