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USING INERTIAL MEASUREMENT UNIT'S (IMU) AND AUGMENTED REALITY (AR) VIDEO TRACKING TO CALCULATE THE BICYCLE ROLL ANGLE
Adrian Cooke, Maarten Bonnema, Bart Koopman
Session: Poster session II
Session starts: Thursday 24 January, 16:00
Adrian Cooke (University of Twente)
Maarten Bonnema (University of Twente )
Bart Koopman (University of Twente )
Abstract:
The goal of this study is to use the Augmented Reality Tool Kit (ARToolKit[1]) video tracking system with Inertial Measurement Units (IMU) to measure the roll angle on a bicycle. The research forms part of the Slimme Ondersteunde FIEts (SOFIE, intelligent assisted bicycles) project (http://mobilitylabtwente.nl/sofie) at the University of Twente. The SOFIE project is investigating how to make bicycles safer for elderly people and bicycle instrumentation is an important part of the research plan.
The Inertial Measurement Unit (IMU) systems are being used extensively in experimental research on human subjects. Over the last few years the accuracy of these systems have increased but they still suffer from problems of drift and magnetic interference. This presentation wishes to compare the accuracy of a modern Inertial Measurement Unit with a video processing marker tracker system using ARToolKit and a standard USB Webcam.
The AR Tracker system is traditionally used for Augmented Reality applications such as gaming and education. It has been shown that for certain applications IMU's are a viable system to use for kinematic research [2]. For the roll angle calculation on a bicycle, IMU's alone do not give enough resolution. These two systems are compared to the Visualeyez VZ-4000 optical tracker system, which is assumed to be the golden standard. A sensor fusion algorithm is then developed to use the AR Tracker and IMU information to improve the accuracy of the roll angle measurements on a bicycle.
Results of experiments designed to compare the accuracy and usability of the systems will be discussed. This will give an analysis of the difference between the AR Markers and IMU to the Visualeyez. Additionally preliminary results of the sensor fusion algorithm (using the IMU and AR Markers) will be given.