ME780 – Nonlinear State Estimation for Robotics and Computer Vision – Spring 2017

Course Syllabus

Week 1:

• Overview of nonlinear State Estimation: slides      video
• Rotations and Transformations: slides    video

Week 2:

• Differential Calculus of 3D Orientations: slides     video-part-1  video-part-2
• Computer Vision, Landmark Feature Tracking: slides     video

Week 3:

• Homework 1      slides     video

Week 4:

• Probability Review, Linear Least Squares, and Estimator Properties: slides video1 video2 video3
• Factor Graphs and Nonlinear Least Squares: slides    video

Week 5:

• Solving Sparse Systems and Square Root Form: slides    video
• Marginalization and Sliding Window Estimation: slides    video

Week 6:

• Homework 2    slides
• Modeling IMU residual terms and noise characterization:   slides   video

Week 7:

• Modeling Camera Residual Terms:    slides    video  Video 2
• Modeling Absolute and Relative Pose Residuals and Point Cloud Scan Registration:    slides    video     Video 2

Week 8:

• Sensor Calibration:  slides    video
• Landmark Based Visual Inertial Odometry and SLAM:    slides    video

Week 9:

• Homework 3   video

Week 10:

• Direct Methods in Visual Odometry:  slides    video