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

• Grant number: 14/08432-0
• Support Opportunities: Research Grants - eScience and Data Science Program - Regular Program Grants
• Start date: January 01, 2015
• End date: June 30, 2017
• Field of knowledge: Engineering - Electrical Engineering - Industrial Electronics, Electronic Systems and Controls
• Principal Investigator: Marco Henrique Terra
• Grantee: Marco Henrique Terra
• Host Institution: Escola de Engenharia de São Carlos (EESC). Universidade de São Paulo (USP). São Carlos , SP, Brazil
• City of the host institution: São Carlos
• Associated 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

Abstract

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)

Scientific publications

(4)

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

CHAVEZ-FUENTES, JORGE R.; MAYTA, JORGE E.; COSTA, EDUARDO F.; TERRA, MARCO H.. Stochastic and exponential stability of discrete-time Markov jump linear singular systems. SYSTEMS & CONTROL LETTERS, v. 107, p. 92-99, SEP 2017. (14/08432-0, 13/19380-8)

INOUE, ROBERTO S.; GUIZILINI, VITOR; TERRA, MARCO H.; RAMOS, FABIO; BICCHI, A; OKAMURA, A. Markovian Jump Linear Systems-based filtering for Visual and GPS Aided Inertial Navigation System. 2017 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS), v. N/A, p. 7-pg., 2017-01-01. (14/50851-0, 15/18085-8, 14/08432-0)

DE JESUS, GILDSON Q.; INOUE, ROBERTO S.; TERRA, MARCO H.. Information filtering and array algorithms for discrete-time Markovian jump linear systems subject to parametric uncertainties. INFORMATION SCIENCES, v. 369, p. 287-303, NOV 10 2016. (14/08432-0)

INOUE, ROBERTO SANTOS; TERRA, MARCO HENRIQUE; CERRI, JOAO PAULO. Extended robust Kalman filter for attitude estimation. IET Control Theory and Applications, v. 10, n. 2, p. 162-172, JAN 19 2016. (14/08432-0)