Magnetometer-Free IMU-Based Joint Axis Calibration and Estimation

惯性测量装置 稳健性(进化) 校准 计算机科学 算法 计算机视觉 平滑的 人工智能 职位(财务) 加速度计 控制理论(社会学) 数学
作者
Linhang Ju,Di Shi,Lufan Mo,Yanjun Shi,Wuxiang Zhang
标识
DOI:10.1109/robio54168.2021.9739334
摘要

According to anatomic equivalent relation, the position of the joint center cannot be measured directly, so calibration of the joint attaches great significance to human motion analysis. Several algorithms have coped with it, however, algorithm complexity and calibration speed with accurate human model make it tough to widely apply. Hence, a modified calibration method is proposed to deal with these problems, where none of jigs, other equipment, or specified action are required in the calibration process. As the main contribution, the robustness and convergence rate are increased while the error in calibration with data of IMU is reduced, and Levenberg-Marquart method is used to calculate joint axes and minimize error. Compared to Gauss-Newton, Levenberg-Marquart has strong convergence and robustness, even if the initial position value is far from the actual position or if the determinant matrix is close to zero. Subsequently, a polynomial interpolation compensates the error caused by the serrated points. Finally, an experiment makes validation of this method. The result indicates that the algorithm converges within four iterations and the error is almost close to zero. Moreover, IMU can be installed arbitrarily since magnetometer-free. Online pre-processing of data and smoothing of anomalous velocity sawtooth points allows the IMU to be easily applied to exoskeletons and human motion intent recognition.

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
汉堡包应助ww采纳,获得10
1秒前
llcssk给llcssk的求助进行了留言
2秒前
聪明不弱发布了新的文献求助10
2秒前
2秒前
2秒前
隐形曼青应助wll5695采纳,获得10
3秒前
清秀三问完成签到,获得积分10
3秒前
3秒前
3秒前
3秒前
科研通AI6.2应助受不了12345采纳,获得10
3秒前
又又发布了新的文献求助10
4秒前
余歌完成签到,获得积分20
4秒前
4秒前
共享精神应助聪明山芙采纳,获得10
5秒前
5秒前
可爱香魔完成签到,获得积分10
5秒前
5秒前
wang完成签到,获得积分10
5秒前
5秒前
5秒前
干净的琦应助感动清炎采纳,获得150
6秒前
欣赏春天发布了新的文献求助10
6秒前
Desamin完成签到,获得积分10
6秒前
CipherSage应助典雅采珊采纳,获得10
7秒前
我是老大应助鲁鲁采纳,获得10
7秒前
7秒前
啊汪~发布了新的文献求助10
7秒前
towanda发布了新的文献求助10
7秒前
8秒前
咸蜜厘不躬完成签到,获得积分10
8秒前
8秒前
chu完成签到,获得积分10
9秒前
xixi完成签到,获得积分10
9秒前
藏羚羊完成签到,获得积分10
9秒前
Tina完成签到,获得积分10
9秒前
科研通AI6.1应助安婷fly采纳,获得10
9秒前
科研通AI6.3应助Xuan采纳,获得10
10秒前
科目三应助m大叔大婶采纳,获得10
10秒前
10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
Picture this! Including first nations fiction picture books in school library collections 2000
The Cambridge History of China: Volume 4, Sui and T'ang China, 589–906 AD, Part Two 1500
Cowries - A Guide to the Gastropod Family Cypraeidae 1200
Quality by Design - An Indispensable Approach to Accelerate Biopharmaceutical Product Development 800
ON THE THEORY OF BIRATIONAL BLOWING-UP 666
Signals, Systems, and Signal Processing 610
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6391720
求助须知:如何正确求助?哪些是违规求助? 8207109
关于积分的说明 17372021
捐赠科研通 5445325
什么是DOI,文献DOI怎么找? 2878940
邀请新用户注册赠送积分活动 1855362
关于科研通互助平台的介绍 1698542