Evidence map›Paper›PMID 41149190›Full record

ArticleBiomimetics (Basel, Switzerland)2025

PteroBot: A Forest Exploration Robot Bioinspired by Pteromyini Gliding Mechanism.

Minghao Fan, Jiayi Wang, Tianyi Liu, Ze Ren, Guoniu Zhu, Jin Ma

Abstract read
In one paragraph

Article in Biomimetics (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

Minghao FanSchool of Automation and Intelligent Sensing, Shanghai Jiao Tong University, Shanghai 200240, China.ORCID 0009-0002-7790-8706
Jiayi WangSchool of Automation and Intelligent Sensing, Shanghai Jiao Tong University, Shanghai 200240, China.
Tianyi LiuSchool of Automation and Intelligent Sensing, Shanghai Jiao Tong University, Shanghai 200240, China.
Ze RenSchool of Automation and Intelligent Sensing, Shanghai Jiao Tong University, Shanghai 200240, China.
Guoniu ZhuCollege of Intelligent Robotics and Advanced Manufacturing, Fudan University, Shanghai 200433, China.
Jin MaSchool of Automation and Intelligent Sensing, Shanghai Jiao Tong University, Shanghai 200240, China.ORCID 0000-0002-6640-3000

Funding

National Key Research and Development Program of China No. 2023YFB3710803National Natural Science Foundation of China No.52375254National Natural Science Foundation of China No. 62472272National Natural Science Foundation of China No. U23B20102
6 · The paper itself

Abstract

Forests are critical ecosystems that play a fundamental role in supporting biodiversity and maintaining climate stability. However, forest monitoring and exploration present huge challenges due to the vast scale and complex terrain. This paper proposes a novel bionic robot, PteroBot, designed to support a new paradigm for forest exploration inspired by the locomotion of Pteromyini. PteroBot is capable of regulating its gliding posture via a flexible membrane, enabling low-energy and low-disturbance mobility within forest environments. An adaptive gliding control system tailored to the robot's structure is developed and its effectiveness is validated through aerodynamic analysis, simulation, and experimental testing. Results show that under a cascaded closed-loop attitude controller, PteroBot achieves an average glide ratio of 2.02 and demonstrates controllable turning via attitude modulation. Additionally, comparative tests with UAVs demonstrate that PteroBot offers significant advantages in energy efficiency and acoustic disturbance. Experimental outcomes confirm that PteroBot offers a biologically inspired and ecologically compatible solution for forest exploration, with strong potential in applications such as environmental monitoring, habitat assessment, and covert reconnaissance.

Indexed as

artificial intelligencebioinspired roboticsforest explorationgliding attitude controlmultimodal perception

Identifiers

PMID41149190
PMCPMC12561732

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.