- Course：Navigation of Autonomous Robots (2019)
|Year 2019: From 10th April Week 10-18 Wed. Class 1 & Fri. Class 4 Building A 308 Language: English|
|Year 2018: From 10th March Week 1-8 Wed. Class 1 & Fri. Class 4 Building A 308 Language: English|
- Introduction to Mobile Robots
- Introduction to Probabilistic Robotics
- Bayes Filter Implementations Kalman Filters
- Kalman Filter Implementations Localization
- Bayes Filter Implementations: Discrete Filters: Histogram Filter，Particle Filter
- Partilce Filter Application：Monte Carlo Localization
- Simultaneous Localization and Mapping
- Rigid Body Motion
- Lie Group & Lie Algebra
- Camera Model & Nonlinear Optimization
- Visual Odometry: Direct & Feature-based
- Front-end & Back-end
- Loop Detection
- Mapping & SLAM future
- Motion Planning & Final Project
- Navigation of Mobile Robots. (2011-2017)
Textbook: Probabilistic Robotics, Sebastian Thrun, Wolfram Burgard, Dieter Fox.
Contents: Introduction of different kinds of mobile robots, Parameter/Non Parameter based Bayes Filters, Monte Carlo Localization, EKF based Localization, EKF-SLAM, FastSLAM, RGBD-SLAM, and Sample-based Motion Planning
- Computer Vision. (2009-2010)
Textbook: Digital Image Processing, Kenneth R. Castleman.
Computer Vision: a modern approach,David A. Forsyth, & Jean Ponce.