USE OF INERTIAL MEASUREMENT UNITS (IMU) FOR KIN-EMATIC ANALYSIS OF JOINTS
Inertial Measurement Unit (IMU) is an electronic device composed of accelerome-ter and gyroscope sensors. The accelerometer is used to measure linear acceleration while the gyroscope is used to measure angular (angular) velocity. In the last decade, micro-electromechanical-based IMUs (MEMS) have bec...
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Main Author: | |
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Format: | Final Project |
Language: | Indonesia |
Subjects: | |
Online Access: | https://digilib.itb.ac.id/gdl/view/67439 |
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Institution: | Institut Teknologi Bandung |
Language: | Indonesia |
Summary: | Inertial Measurement Unit (IMU) is an electronic device composed of accelerome-ter and gyroscope sensors. The accelerometer is used to measure linear acceleration while the gyroscope is used to measure angular (angular) velocity. In the last decade, micro-electromechanical-based IMUs (MEMS) have become the main alternative as a substitute for Optical Motion Capture. Wireless inertial measurement technology is re-quired in such applications. Various IMU manufacturers are competing to create a mul-tisensory IMU platform where the system is already integrated with a centralized trans-mitter module and is available with data processing algorithms and filters. Therefore, it has a relatively expensive price.
In this Final Project, the author developed an algorithm to interpret the measure-ment data of two IMU, especially the joint angle formed by two rods to create a simple multisensory IMU system platform using two singles wireless IMU WitMotion BWT61CL. The function of this algorithm is to analyse joint kinematics through joint angle measurement. The algorithm was validated with the industrial robot arm Yaskawa Motoman SIA10D located at ITB. The algorithm was successfully created by the authors using Matlab programming which is equipped with complementary filters so that noise and drift can be significantly eliminated. Through testing, the average value of RMSE, percent error, and drift are relatively small, namely drift of 0.00644°/s, percent error of 2.519%, and RMSE of 0.79°. So, it can be concluded that the algorithm is feasible to use or validated. |
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