Kinetostatic Modeling of Continuum Delta Robot With Variable Curvature Continuum Joints

工作区 常曲率 曲率 机器人 计算机科学 物理 控制理论(社会学) 结构工程 数学 工程类 几何学 人工智能 控制(管理)
作者
Xiang Wang,Yue Ding,Lingyun Zeng,Chuanxiang Zhu,Baibo Wu,Kai Xu
出处
期刊:Journal of Mechanisms and Robotics [ASME International]
卷期号:15 (3) 被引量:4
标识
DOI:10.1115/1.4056954
摘要

Abstract Continuum robots have attracted lots of attention due to their structural compliance, manipulation dexterity, and design compactness. To extend the application scenarios, a slender continuum robot, the CurviPicker, was developed for low-load medium-speed pick-and-place tasks in a previous study. To improve the payload capacity and positioning accuracy of the CurviPicker, a novel Continuum Delta Robot (CDR) was then proposed with three dual-continuum-joint translators in a preliminary investigation. However, the initial version of the CDR did not fully utilize the bending ranges of its continuum joints. In addition, while being modeled using the constant curvature assumption for the continuum joints, the CDR shows lowered positioning accuracy for heavier objects, as the CDR’s continuum joints diverge from the assumed constant curvature shapes. In this paper, the design of the CDR was re-optimized to enable wider bending ranges of the continuum joints (>90 deg) to generate an enlarged workspace, taking into consideration several possible structural interferences. Furthermore, a kinetostatic model is derived based on the Cosserat rod theory to reduce the positioning errors caused by the external loads. The experimental result showed that the workspace is enlarged to approximately 9.47 × 107 mm3 compared with the volume of 6.57 × 107 mm3 of the initial version. Within this enlarged workspace, the average positioning error with a 1000-g load was reduced to 1.93 mm, compared with 4.43 mm obtained by the previous constant curvature assumption.
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
MEME发布了新的文献求助10
1秒前
1秒前
情怀应助LSH970829采纳,获得10
1秒前
CHINA_C13发布了新的文献求助10
4秒前
Mars发布了新的文献求助10
5秒前
哈哈哈完成签到,获得积分10
5秒前
玛卡巴卡应助平常的毛豆采纳,获得100
6秒前
默默的青旋完成签到,获得积分10
7秒前
10秒前
搜集达人应助淡淡采白采纳,获得10
10秒前
高高代珊完成签到 ,获得积分10
11秒前
gmc发布了新的文献求助10
12秒前
12秒前
13秒前
善学以致用应助Mian采纳,获得10
13秒前
学科共进发布了新的文献求助60
14秒前
LWJ完成签到 ,获得积分10
14秒前
14秒前
缓慢的糖豆完成签到,获得积分10
15秒前
阉太狼完成签到,获得积分10
15秒前
16秒前
soory完成签到,获得积分10
17秒前
任性的傲柏完成签到,获得积分10
17秒前
lwk205完成签到,获得积分0
17秒前
18秒前
一一完成签到,获得积分10
18秒前
18秒前
18秒前
高中生完成签到,获得积分10
19秒前
19秒前
19秒前
希望天下0贩的0应助TT采纳,获得10
20秒前
xxegt完成签到 ,获得积分10
20秒前
21秒前
爱吃泡芙发布了新的文献求助10
21秒前
susu完成签到,获得积分10
23秒前
会神发布了新的文献求助10
23秒前
KK完成签到,获得积分10
24秒前
充电宝应助justin采纳,获得10
26秒前
27秒前
高分求助中
Continuum Thermodynamics and Material Modelling 3000
Production Logging: Theoretical and Interpretive Elements 2700
Social media impact on athlete mental health: #RealityCheck 1020
Ensartinib (Ensacove) for Non-Small Cell Lung Cancer 1000
Unseen Mendieta: The Unpublished Works of Ana Mendieta 1000
Bacterial collagenases and their clinical applications 800
El viaje de una vida: Memorias de María Lecea 800
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 基因 遗传学 物理化学 催化作用 量子力学 光电子学 冶金
热门帖子
关注 科研通微信公众号,转发送积分 3527990
求助须知:如何正确求助?哪些是违规求助? 3108173
关于积分的说明 9287913
捐赠科研通 2805882
什么是DOI,文献DOI怎么找? 1540119
邀请新用户注册赠送积分活动 716941
科研通“疑难数据库(出版商)”最低求助积分说明 709824