Professor: Marek A. Perkowski, Electrical Engineering.
ADVANCED EMBEDDED ROBOTCS
This class starts from easy basic logic and robot control problems and continues with advanced topics such as
robot morality based on modal logic.
All these theories are used in practical robot projects.
Goal of the class.
Students should learn elementary, medium and some advanced topics in robot vision and perception
to be used in software, hardware and integration/robotic projects.
This is the second class in robotics but can be taken with no prerequisities in case
that the students knows programming.
Students should get practical understanding how robot vision algorithms are used in robot systems.
Where is this knowledge useful?
Previous students who have done projects found this class useful to find industrial positions in the
following areas: robot vision, flexible automation systems with vision, medical image processing,
hardware design of image processors, bank image processing,
general software design, industrial board-level design, design automation.
Software used in class depends on every year projects.
LECTURES AND MATERIALS FOR PROJECTS AND CLASS
B1. PROPOSITIONAL LOGIC AND MODAL LOGIC IN ROBOTICS.
- introduction to logic.
- Basic Logic.
- Reasoning Agents.
- Representation and Logic.
- First Order Logic. ADDITIONAL.
- Boolean Logic.
- Robot Morality and Review
of classical logic.
- Introduction to Satisfiability.
- Wumpus world in Ppropositional logic.
A muddy children and intro to modal logic.
Wise Men, Muddy Children, Logic Puzzles and Modal Logic.
- The Narrow Bridge Universe.
- sum and product problem.
B2. KNOWLEDGE REPRESENTATION AND PLANNING WITH FIRST ORDER LOGIC.
- Introductio to Knowledge representation.
- Introduction to Planning.
- From propositional to predicate logic.
- First order logic.
- Inference in first order logic.
Examples of FIRST ORDER theorem-proving and Colonel West.
- Artificial Intelligence in Logic. Prolog Language Tutorial.
- ROBOT MORALITY. An easy introduction.
- Prolog Planning Monkey and Banana.
- Modal and Deontic Logic Derivations.
B.3. MOBILE ROBOTS.
B.10.1. Mobile robots.
Class about autonomous mobile robots. In PDF.
Homework in mobile robot kinematics. In PDF format.
Measurement and correction of systematic odometry errors in mobile robots. Paper in PDF format.
- Paper in PDF.
Structural Properties and Classification of Kinematic and Dynamic Models of Wheeled Mobile Robots.
B.4. PROBABILISTIC ROBOTICS. LOCALIZATION. PLANNING. MAPPING.
B.4.1. Robot Localization and related topics.
Thesis by Philip Kedrowski about Self-building global maps for autonomous navigation.
In PDF format.
Lecture from CMU about Mapping. Slides in PPT format.
Mobile robot positioning using sensor. In PDF.
Paper in PDF about Monte Carlo localization for mobile robots.
Paper on Experimental Comparison of localization methods in PDF.
Bayesian estimation and Kalman filtering: A Unified framework for Mobile
Robot Localization. Paper in PDF.
- Fingerprint for mobile robot localization in PDF.
Dynamic Markov localization approach, by Burgard, Derr, Fox and Cremers. Paper
in PDF format.
B.4.3. Robot Path Planning and related topics.
Navigation and Metric Path Planning.
Lecture from CMU about Path planning for mobile robots. Slides in PDF format.
- Paper about path planning for a mobile robot. In PDF.
B.4.4. Motion Planning and Robot Learning.
- New Paradigm for robot learning. In PDF.
B.4.5. Robot Obstacle Avoidance and related topics.
Paper about fast obstable avoidence based on vector field histogram. In PDF.
A.12. STATIONARY ROBOTS.
A.12.1. Motion Planning for stationary robots.
Motion planning methods good for stationary robot with hands. In PDF.
- Motion Planning that may be applied to
any kind of robots. PDF.
A3. ROBOT THEATRE PROJECT
A.2.6. Vision for Robot Localization
- Vision for robot localization by Ulrich. Paper in PDF.
A.2.7. Region Segmentation
- Region Segmentation. Slides in PDF format.
- Slides in PDF about wavelets.
- Beyond wavelets and JPEG 2000. Slides in PPT format.
Lecture about Tracking Devices for humans, for instance built into glasses. In PDF format.
A.2.10. OPENCV and Examples of OPENCV Projects
Thesis by Mikhail Pivtoraiko about using OpenCV on Stanton board. In Word format.
- Instruction about using OpenCV. In PPT format.
- Contact to Sam Siziliano who is OpenCV expert.
- Email from Anthony Kautz
who build speech for robot and worked on OpenCV. Helpful. But may be obsolete now. In txt format.
- cv096.dll DLL from student Jeff for project.
- cxcore096.dll DLL from student Jeff for project.
A.6. MATLAB AND MATLAB IN ROBOT VISION.
Lectures on Matlab. Lecture 1. Introduction to Matlab.
Lectures on Matlab. Lecture 2. More Matlab Programming.
Lectures on Matlab. Lecture 3. Finishing with Matlab.
Lectures on Matlab. Lecture 4. Finishing with Matlab.
- Lecture on Introduction and Control Basic to Matlab. In PDF.
- The same lecture in PPT.
- Matlab Primer in PDF.
Introduction to Matlab in PPT.
Matlab two-dimensional plots in PPT.
Matlab Script and Function files in PPT.
- Simple Programming in Matlab in PPT.
Solution of non-linear algebraic equations in Matlab. PPT format.
- F2D.mat Matlab Examples.
- F3D.mat F2D.mat Matlab Examples.