State Estimation for Flying Robots
Semester Project EPFL
This project is about developing and characterizing a state estimator using a Kalman filter for sensor fusion for a fixed-wing UAV. The filter should rely on an existing hardware (see http://lis.epfl.ch/smavs) which includes the following sensors: 3-axis MEMS rate gyros and 3-axis accelerometers, barometer and airspeed sensors, 3-axis magnetometers and a GPS. The full filter should be implemented in a cascaded configuration, and should provide an accurate estimation of the orientation and heading in a first stage, position and velocity in a second stage. It will be coded in C, and will have to run in real-time on the embedded auto-pilot. The limited computational power of the available microcontroller tdsPIC33) will have to be taken into account during the design. The obtained results will be compared to the output of a commercially available module providing the same information (Xsens MTi-G). The project can be carried out by two students, with the following task distribution : At first, both students will work on separate implementations, based on an existing filter. The first student will include the 3-axis magnetometer to the filter while the second student will include the GPS speed and heading. Both students will then compare the results of their different approaches. They will then work together on the second part of the filter, using the full position information from the GPS for position estimation.