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Attitude and heading reference system based on recursive robust Kalman filter implemented in FPGA

Grant number: 14/08432-0
Support type:Research Grants - eScience and Data Science Program - Regular Program Grants
Duration: January 01, 2015 - June 30, 2017
Field of knowledge:Engineering - Electrical Engineering
Principal Investigator:Marco Henrique Terra
Grantee:Marco Henrique Terra
Home Institution: Escola de Engenharia de São Carlos (EESC). Universidade de São Paulo (USP). São Carlos, SP, Brazil
Assoc. researchers:Denis Fernando Wolf ; Fernando Santos Osório ; Kalinka Regina Lucas Jaquie Castelo Branco ; Roberto Santos Inoue ; Valdir Grassi Junior
Associated scholarship(s):16/01899-5 - Attitude and heading reference system based on recursive robust Kalman filter implemented in FPGA, BP.PD


This research project aims to develop an attitude, orientation and position reference system based on a recursive robust Kalman filter (RRKF) we are proposing. This RRKF performs better than the standard Kalman filter to the data fusion from a low cost inertial measurement unit (IMU). This type of IMU lacks the quality of signals measured in costly IMU. The main contribution of this research is the development of an RRKF array algorithm for the implementation of the fixed point proposed system in an FPGA (Field Programmable Gate Array). This project will be implemented in partnership with the Intelligent Systems Laboratory (LASI), with the Mobile Robotics Laboratory (LRM) both at USP - São Carlos and Scania Latin America Ltda. These laboratories develop research in the areas of robotics, robust control and filtering, and estimation of attitude and position of autonomous vehicles. These two laboratories and the Scania enterprise (comprising the units based in Brazil and Sweden) have been developing research related to autonomous trucks. The results of this proposal will be applied at this R&D project being developed in partnership with Scania. (AU)

Articles published in Agência FAPESP about the research grant
FAPESP issues new call for eScience multidisciplinary research proposals 
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