Citation: Zhu, H.; Li, X.; Wang, L.;
Chen, Z.; Shi, Y.; Zheng, S.; Li, M.
IMU Motion Capture Method with
Adaptive Tremor Attenuation in
Teleoperation Robot System. Sensors
2022, 22, 3353. https://doi.org/
10.3390/s22093353
Academic Editors: Enrico Vezzetti,
Andrea Luigi Guerra, Gabriele
Baronio, Domenico Speranza and
Luca Ulrich
Received: 23 March 2022
Accepted: 25 April 2022
Published: 27 April 2022
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Article
IMU Motion Capture Method with Adaptive Tremor
Attenuation in Teleoperation Robot System
Huijin Zhu
1
, Xiaoling Li
1,
*, Long Wang
1
, Zhangyi Chen
1
, Yueyang Shi
1
, Shuai Zheng
2
and Min Li
1
1
School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an 710000, China;
zhhjjym@stu.xjtu.edu.cn (H.Z.); wangl521@stu.xjtu.edu.cn (L.W.); 3120101240@stu.xjtu.edu.cn (Z.C.);
victories@stu.xjtu.edu.cn (Y.S.); min.li@mail.xjtu.edu.cn (M.L.)
2
School of Software Engineering, Xi’an Jiaotong University, Xi’an 710000, China; shuaizheng@xjtu.edu.cn
* Correspondence: xjtulxl@mail.xjtu.edu.cn; Tel.: +86-130-0295-1718
Abstract:
Teleoperation robot systems can help humans perform tasks in unstructured environments.
However, non-intuitive control interfaces using only a keyboard or joystick and physiological tremor
reduce the performance of teleoperation. This paper presents an intuitive control interface based on
the wearable device gForcePro+ armband. Two gForcePro+ armbands are worn at the centroid of
the upper arm and forearm, respectively. Firstly, the kinematics model of the human arm is estab-
lished, and the inertial measurement units (IMUs) are used to capture the position and orientation
information of the end of the arm. Then, a regression model of angular transformation is developed
for the phenomenon that the rotation axis of the torsion joint is not perfectly aligned with the limb
segment during motion, which can be applied to different individuals. Finally, to attenuate the
physiological tremor, a variable gain extended Kalman filter (EKF) fusing sEMG signals is developed.
The described control interface shows good attitude estimation accuracy compared to the VICON
optical capture system, with an average angular RMSE of 4.837
◦
±
1.433
◦
. The performance of the
described filtering method is tested using the xMate3 Pro robot, and the results show it can improve
the tracking performance of the robot and reduce the tremor.
Keywords: IMU; regression model; physiological tremor; EKF; sEMG signal; teleoperation system
1. Introduction
Robotic manipulators can use teleoperation to interact with a wide array of objects
and scenarios in unstructured environments [1]. Through teleoperation, human cognitive
abilities can be used to assist robots in handling decisions that are particularly difficult for
autonomy [
2
]. Robots have a wide range of applications and are now entering the daily life
of human beings; it is becoming more likely that novices will work with robots rather than
robotic experts [
3
,
4
]. In robot teleoperation, a major area of research focuses on providing
a control interface that is intuitive and easily preserves situation awareness [
5
]. Hence,
teleoperation can be accessed by novices with less training time. A teleoperation control
interface can be visited with hand motions as opposed to joysticks and point-and-click
interfaces, as they are natural movements to the teleoperator [6].
The optical tracking system includes multiple cameras and depth cameras. Multi-
camera motion capture systems track active or passive markers attached to anatomical areas
of the body to measure joint motion. Multi-camera is considered the measurement standard,
providing very accurate motion estimates, and the results of other motion capture systems
are often compared and validated against the multi-camera motion capture results [
7
].
The depth camera can detect the depth of field distance in the shooting space. Microsoft
Kinect and Leap Motion controller are two different depth motion capture systems used
for upper limb motion estimation [
8
]. Both systems use the human skeleton to track 3D
motion without the use of any markers. When using a depth camera system, it is possible
for the user to be occluded by other people or objects in the system’s field of view, and
Sensors 2022, 22, 3353. https://doi.org/10.3390/s22093353 https://www.mdpi.com/journal/sensors
