Fiber-optic-based force and shape sensing in surgical robots: a review

机器人 机电一体化 机器人学 计算机科学 光纤 人工智能 电磁干扰 工程类 控制工程 电子工程 电信
作者
Qi Jiang,Jihua Li,Danish Masood
出处
期刊:Sensor Review [Emerald Publishing Limited]
卷期号:43 (2): 52-71 被引量:26
标识
DOI:10.1108/sr-04-2022-0180
摘要

Purpose With the increasing development of the surgical robots, the opto-mechatronic technologies are more potential in the robotics system optimization. The optic signal plays an important role in opto-mechatronic systems. This paper aims to present a review of the research status on fiber-optic-based force and shape sensors in surgical robots. Design/methodology/approach Advances of fiber-optic-based force and shape sensing techniques in the past 20 years are investigated and summarized according to different surgical requirement and technical characteristics. The research status analysis and development prospects are discussed. Findings Compared with traditional electrical signal conduction, the phototransduction provides higher speed transmission, lower signal loss and the immunity to electromagnetic interference in robot perception. Most importantly, more and more advanced optic-based sensing technologies are applied to medical robots in the past two decades because the prominence is magnetic resonance imaging compatibility. For medical robots especially, fiber-optic sensing technologies can improve working security, manipulating accuracy and provide force and shape feedback to surgeon. Originality/value This is a new perspective. This paper mainly researches the application of optical fiber sensor according to different surgeries which is beneficial to learn the great potential of optical fiber sensor in surgical robots. By enumerating the research progress of medical robots in optimization design, multimode sensing and advanced materials, the development tendency of fiber-optic-based force and shape sensing technologies in surgical robots is prospected.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
anthony完成签到,获得积分10
刚刚
刚刚
乖猴猴发布了新的文献求助10
刚刚
1秒前
xing_xing应助123采纳,获得20
1秒前
Ronnie完成签到,获得积分20
1秒前
fujunhao完成签到,获得积分10
2秒前
别和我的水完成签到,获得积分10
2秒前
Eric完成签到,获得积分10
2秒前
曹沛岚完成签到,获得积分10
2秒前
AHR完成签到,获得积分10
3秒前
OK应助结实的半双采纳,获得200
3秒前
3秒前
3秒前
mimi发布了新的文献求助10
3秒前
打打应助欢欢欢乐乐乐乐采纳,获得10
3秒前
海上森林的一只猫完成签到 ,获得积分10
3秒前
子车代芙发布了新的文献求助10
4秒前
孜然西瓜完成签到,获得积分10
4秒前
在水一方应助Explosion采纳,获得10
4秒前
4秒前
拼搏的春子完成签到,获得积分10
5秒前
Accelerator完成签到,获得积分10
5秒前
微笑主宰完成签到,获得积分10
5秒前
华仔应助甜田采纳,获得10
5秒前
Yuxuan发布了新的文献求助10
5秒前
ning发布了新的文献求助30
5秒前
森活鱼块完成签到,获得积分10
5秒前
hsn完成签到,获得积分10
5秒前
qiqi完成签到,获得积分10
5秒前
Ava应助Jane采纳,获得10
6秒前
Ronnie发布了新的文献求助10
6秒前
宋子琛完成签到,获得积分10
6秒前
谦让问兰完成签到,获得积分10
6秒前
yumuhai发布了新的文献求助10
6秒前
6666应助anthony采纳,获得10
6秒前
6秒前
实在有难度完成签到 ,获得积分10
6秒前
6秒前
刘屁屁完成签到 ,获得积分10
6秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Nine new races of Peronospora manshurica found on soybeans in the Midwest 1000
Essentials of Carbohydrate Chemistry and Biochemistry, 4th Edition 600
Organizational Behavior 510
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Eudora Welty and Modern Media 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 计算机科学 化学工程 工程类 有机化学 物理 复合材料 生物化学 内科学 细胞生物学 基因 遗传学 免疫学 冶金 光电子学 癌症研究
热门帖子
关注 科研通微信公众号,转发送积分 7773061
求助须知:如何正确求助?哪些是违规求助? 9315213
关于积分的说明 20344099
捐赠科研通 7358801
什么是DOI,文献DOI怎么找? 3317136
关于科研通互助平台的介绍 2465678
邀请新用户注册赠送积分活动 2332256