移动机器人导航理论

  • 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

Course Outline:

  1. Introduction to Mobile Robots
  2. Introduction to Probabilistic Robotics
  3. Bayes Filter Implementations Kalman Filters
  4. Kalman Filter Implementations Localization
  5. Bayes Filter Implementations: Discrete Filters: Histogram Filter,Particle Filter
  6. Partilce Filter Application:Monte Carlo Localization
  7. Simultaneous Localization and Mapping
  8. Rigid Body Motion
  9. Lie Group & Lie Algebra
  10. Camera Model & Nonlinear Optimization
  11. Visual Odometry: Direct & Feature-based
  12. Front-end & Back-end
  13. Loop Detection
  14. Mapping & SLAM future
  15. 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.