May 2019 - Professor Davi Santos

1 MP-208: Optimal Filtering

Week 11: Application: Navigation Using Fiducial Markers and Inertial Sensors

This week, I formule an aerospace/robotic application for the continuous-discrete filters. It consists of the navigation of a 6DOF platform equipped with inertial sensors (accelerometers and rate-gyros) as well as a camera. The scenario contains many fiducial markers placed at known positions. The visual fiducial system is assumed to be available; it provides indirect measures of the visible markers’ relative position w.r.t. the camera. In this application, we have to estimate the platform position, velocity, attitude, as well as the accelerometer and rate-gyro biases. Material: Continue→

MP-208: Optimal Filtering

Week 10: Unscented Kalman Filter

This week, we present the discrete and continuous-discrete formulations of the uncented Kalman filter. Material: Chapter 7 – Part I: Discrete Unscented Kalman Filter Chapter 7 – Part II: Continuous-Discrete Unscented Kalman Filter Computational Exercise #3: CDUKF and CDEKF Previous post of this course: Week 1: Syllabus + Introduction Week 2: Linear Algebra + Linear Systems Week 3: Set + Probability + Random Variables Week 4: Random Variables + Random Vectors Week 5: Random Vectors + Stochastic Processes Week 6: Stochastic Processes + Parameter Estimation Continue→

Courses

Week 9: Extended Kalman Filter

This week, I present the discrete and continuous-discrete formulations of the extended Kalman filter. This is an approximation of the KF for non-linear systems. Material: Chapter 6 – Part I: Discrete Extended Kalman Filter Chapter 6 – Part II: Continuous-Discrete Extended Kalman Filter Previous post of this course: Week 1: Syllabus + Introduction Week 2: Linear Algebra + Linear Systems Week 3: Set + Probability + Random Variables Week 4: Random Variables + Random Vectors Week 5: Random Vectors + Stochastic Processes Week 6: Stochastic Continue→