A Novel Handheld Bronchoscope Robot With Human–Robot Shared Control Strategy for Pulmonary Examination

Bronchoscope robots have been developed for the early diagnosis of lung diseases. Although they have made some progress in sophisticated design, most still have cumbersome back-end driving systems, adopting electric sliders or mechanical arms to achieve feed motion, and the device cost is also high. Besides, current global navigation strategies also rely on expensive sensors, and these factors limit the popularization of bronchoscope robots in underdeveloped areas. In this article, a low-cost, lightweight, and portable handheld bronchoscope robot is presented. The structural design and kinematics model of the robot are introduced in detail. In addition, a human–robot shared control strategy is proposed, which combines human intervention commands with segmented endoscopic images by the U-net model to achieve safe bronchoscopy. The experimental results show that the robot has good steering ability and flexible maneuvering capability and can go deep into the fifth and higher generation of the bronchus for examination. In addition, bronchoscopy experiments demonstrate that the proposed handheld bronchoscope robot with a human–robot shared control strategy can achieve a better operation level of bronchoscopy than the teleoperation method.

Authors

Institutions

Publication Details

Journal
IEEE/ASME Transactions on Mechatronics
Published
2024-10-07
DOI
https://doi.org/10.1109/tmech.2024.3462454
Citations
2
Primary Topic
Tracheal and airway disorders
Type
article
Field-Weighted Citation Impact
0.84

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Novel Handheld Bronchoscope Robot With Human–Robot Shared Control Strategy for Pulmonary Examination

Rong Xiong, Qin Fang, Haojian Lu, Lilu Liu et al.
2 citations
IEEE/ASME Transactions on Mechatronics
Tracheal and airway disorders
0.84
article

A Novel Handheld Bronchoscope Robot With Human–Robot Shared Control Strategy for Pulmonary Examination

Rong Xiong, Qin Fang, Haojian Lu, Lilu Liu, Jingyu Zhang, Yue Wang, Fei Wang
article en
2 citations

Abstract

Bronchoscope robots have been developed for the early diagnosis of lung diseases. Although they have made some progress in sophisticated design, most still have cumbersome back-end driving systems, adopting electric sliders or mechanical arms to achieve feed motion, and the device cost is also high. Besides, current global navigation strategies also rely on expensive sensors, and these factors limit the popularization of bronchoscope robots in underdeveloped areas. In this article, a low-cost, lightweight, and portable handheld bronchoscope robot is presented. The structural design and kinematics model of the robot are introduced in detail. In addition, a human–robot shared control strategy is proposed, which combines human intervention commands with segmented endoscopic images by the U-net model to achieve safe bronchoscopy. The experimental results show that the robot has good steering ability and flexible maneuvering capability and can go deep into the fifth and higher generation of the bronchus for examination. In addition, bronchoscopy experiments demonstrate that the proposed handheld bronchoscope robot with a human–robot shared control strategy can achieve a better operation level of bronchoscopy than the teleoperation method.

IEEE/ASME Transactions on MechatronicsVol. 30(5)
Harbin Institute of Technology (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 24%
Tracheal and airway disorders
0.84
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.