9dof-orientation-estimation - Various kind of 9 Degrees of freedom IMU orientation estimation algori

The aim of this project is to achieve efficient orientation estimation algorithms using a 9 DOF IMU. We used the iNEMO V2 as IMU; It is the inertial module unit released by ST Microelectronics (official site http://www.st.com/internet/evalboard/product/250367.jsp ). This project is done in cooperation with ST Microelectronics: R&D group, AST Advanced System Technologies / Remote Monitoring (andrea.vitali@st.com). We're two software engineering students of "Università degli studi di Bergamo" ( http://www.unibg.it/ ). The project has started as an academic experience related to "Progetto di Microelettronica" course, and over time it has became an hobby. We developed the following algorithms: - Complementary filter: the simplest way to estimate orientation using a 9DOF IMU. Attached in the "Download" section Matlab and C# sources. - Kalman filter: implementation of Kalman filter using quaternion as system state. Attached in the "Download" section Matlab and C# sources. - AHRS estimation algorithm: this implementation is provided by the project imumargalgorithm30042010sohm ( http://code.google.com/p/imumargalgorithm30042010sohm/ ). We inserted the source as a class into our C# project, fitting it to our IMU (downloadable in the "Download" section). There's also a report of our work attached as pdf file (Italian language). Demonstration videos: http://www.youtube.com/watch?v=p8H2-vkUM0I 2011/05/16: UPLOADED latest improvements achieved during last month. Old versions of Kalman filter, Complementary filter and C# application has been marked with the "OLD" label. 2011/12/29: We are sorry for the long time during which this site has not been maintained: in the latest months we have been busy a lot (inter alia, we got the master's degree in computer engineering). Nevertheless we have continued to work on this project in the spare time; here is below a link to a demonstration video showing our rough first prototype of a motion tracking system. As you can see, there are ONLY two BIG and WIRE CONNECTED marg sensors without the CASE. Besides, some TAPE has been used to keep them fixed on the arm, hence the system is not very precise. The software application is a NOT optimized alpha version and uses a very old version of a quaternion based Complementary Filter. http://www.youtube.com/watch?v=mn8vfYt1U1I&context=C3e2c6f5ADOEgsToPDskKHH6ybFsuhwhsC-CkazIrX Soon we'll be able to post some stuff about this work. Meanwhile, you can of course contact us! See ya in 2012...


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