December 15, 2022

• Have still access to the Canvas page of AMR

December 14, 2022

• Section 11.5 'Image-Based Control Laws' (1st edition 12.4) of 2nd edition (2020) has now a pile of books as example (Fig. 11.6).

December 13, 2022

• Received the evaluation copy of Robot Modelling and Control, 2nd edition (2020), as ebook on my Wiley's bookshelf. Read Chapter 11, Vision-Based Control.
• This chapter is still manipulator based (what to do when you don't have physical contact, so force feedback doesn't work).
• The chapter concentrates on eye-in-hand camera systems, which is chosen to be a single camera with a fixed focal length. So, no depth camera!
• New is the section 11.2, which describes Computer Vision (for grayscale images!). In the 2006 edition this was a whole chapter, now reduced to a section.
• New is the subsection 11.2.2 on Image Features.
• The number of exercises doubled for this chapter.
• Also new is Chapter 14 - Mobile Robots.
• One concentrates on the control equations on for instance the unicycle, differential drive and car-like robot.
• A nice treatment of steering using sinusoids.
• So nice book, but with a clear focus on Control.
• Interesting for the Biomimetic Robots course will be this 2023 book.
• Ordered a evaluation copy of Introduction to Autonomous Robots (Dec 2022).
• The labs of this book are Webots based.
• The labs are developed for the course Advanced Robotics from the University of Colorado Boulder.
• The labs of Introduction to Robotics are far more relevant for us, with reactive behaviors, line following, mapping with lidar and path-planning.
• Started with Chapter 12 - Mapping of Introduction to Autonomous Robots, which also covers RGB-D mapping. It describes ICP, Octomaps and truncated signed distance fields (TSDF). Note that SLAM is covered in Chapter 17.
• Also read Chapter 17. This is a very concise introduction of EKF-SLAM and Graph-SLAM. I am not sure if this works if you are not already familiar with both concepts.
• For using ICP to stitch local RGB-D maps they point to RGB-D Mapping: Using Depth Cameras for Dense 3D Modeling of Indoor Environments (Experimental Robotics, 2014)
• Nice that paper includes (Fig. 4) a 3D map of the well known Intel Lab.

December 12, 2022

• The course of the Australian National University has both bachelor and master entry. Some course, other criteria.
• The course is based on Robot Modelling and Control, 1st edition (2006), while the 2nd edition (2020) already exists.
• This IEEE Review also lists alternative choices. Most are already quite old, except Modern Robotics (2017). Yet, this book is also focused on mechanics and control.
• The 2010 book Computational Principles of Mobile Robotics (2nd edition) would be a better choice.
• Also from CMU: Mobile Robotics (2013). That is a book I don't have.
• The Australian National University course follows a different schedule than the book. The actual schedule of 2022 (12 week / sessions):
  1. Kinematics nil
  2. Odometry Nil
  3. Spatial Variables Nil
  4. Sensors and Probability Nil
  5. Spatial Variables A03: Problem Sheet 01
  6. Visual Odometry A02: Laboratory 02
  7. Stochastic Filters A05: Problem Sheet 02 A08: Mid Semester Quiz
  8. Extended Kalman Filter A04: Laboratory 03
  9. SLAM Nil
  10. Path planning and navigation Nil
  11. Obstacles and Control A06: Laboratory 04
  12. Revision and perspective A07: Problem Sheet 03
• The laboratory work (01-04) is on the independent implementation of SLAM on a small mobile robotic system.

June 15, 2022

• Shree Nayar released the first 8 chapters of his textbook First Principles of Computer Vision

Previous Labbooks

• Labbook2020.html
• Labbook2018.html
• Labbook2017.html
• Labbook2016.html
• Labbook2015.html
• Labbook2014.html
• Labbook2013.html
• Labbook2012.html
• Probabilistic Robotics 2012
• Labbook2010.html
• Labbook2009.html
• Labbook2008.html
• Labbook2007.html
• This Visual Odometry code is Univ. of Maryland project work on a Computer Vision assignment from ETHZ.