Professor: Marek A. Perkowski, Electrical and Computer Engineering.

ADVANCED EMBEDDED ROBOTCS


This is a continuation of Intelligent Robotics I and Intelligent Robotics II, but can be taken without these prerequisities for students who have sufficient background in programming or mechanical engineering (knowledge of one of programming languages such as C, C#, C++, Java or RobotC is expected).
The grading is done only on projects and student presentations. Short quizzes may be expected but they are not graded.
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 may be used in practical robot projects. This quarter the projects are either new, or are continuations of the projects from last quarter. The goal is that students who continue projects will write final conference or journal papers and complete their robots. New students can start a new project of their choice, based on their background and interests.

Goal of the class.


Students should learn elementary, medium and some advanced topics in robot control, robot vision, and human-robot interaction, to be used in software, hardware and integration/robotic projects. Students should get practical understanding how robot vision and robot control algorithms are used in the entire 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.


  1. Software used in class depends on every year projects.
  2. Usually students use language OpenCV for robot vision and Machine Learning, Matlab for all projects and Prolog for planning, problem solving and Human-Robot interaction.
  3. Learning Prolog is not mandatory as it is used only in some projects.
  4. Standard software is C, C++ and Java.
  5. Software used every year depends on the particular project.

LECTURES AND MATERIALS FOR PROJECTS AND CLASS IN YEAR 2014.


B1. PROPOSITIONAL LOGIC AND MODAL LOGIC IN ROBOTICS.


SLIDES FOR CLASS.
  1. introduction to logic.
  2. Basic Logic.
  3. Reasoning Agents.
  4. Representation and Logic.
  5. First Order Logic. ADDITIONAL.
  6. Boolean Logic.
  7. Robot Morality and Review of classical logic.
  8. Introduction to Satisfiability.
  9. Wumpus world in Propositional logic.
  10. A muddy children and intro to modal logic.
  11. Wise Men, Muddy Children, Logic Puzzles and Modal Logic.
  12. The Narrow Bridge Universe.
  13. sum and product problem.

B2. KNOWLEDGE REPRESENTATION AND PLANNING WITH FIRST ORDER LOGIC.


SLIDES FOR CLASS.
  1. Introductio to Knowledge representation.
  2. Introduction to Planning.
  3. From propositional to predicate logic.
  4. First order logic.
  5. Inference in first order logic.
  6. Examples of FIRST ORDER theorem-proving and Colonel West.
  7. Artificial Intelligence in Logic. Prolog Language Tutorial.
  8. ROBOT MORALITY. An easy introduction.
  9. Prolog Planning Monkey and Banana.
  10. Modal and Deontic Logic Derivations.

B.3. MOBILE ROBOTS.

B.10.1. Mobile robots.


PAPERS TO READ FOR CLASS.
  1. Class about autonomous mobile robots. In PDF.
  2. Homework in mobile robot kinematics. In PDF format.
  3. Measurement and correction of systematic odometry errors in mobile robots. Paper in PDF format.
  4. Paper in PDF. Structural Properties and Classification of Kinematic and Dynamic Models of Wheeled Mobile Robots.

B.4. PROBABILISTIC ROBOTICS. LOCALIZATION. PLANNING. MAPPING.


PAPERS TO READ FOR CLASS.

B.4.1. Robot Localization and related topics.

  1. Mobile robot positioning using sensor. In PDF.
  2. Paper in PDF about Monte Carlo localization for mobile robots.
  3. Paper on Experimental Comparison of localization methods in PDF.
  4. Bayesian estimation and Kalman filtering: A Unified framework for Mobile Robot Localization. Paper in PDF.
  5. Fingerprint for mobile robot localization in PDF.
  6. Dynamic Markov localization approach, by Burgard, Derr, Fox and Cremers. Paper in PDF format.

B.4.2. Robot Map Building and related topics.

  1. Thesis by Philip Kedrowski about Self-building global maps for autonomous navigation. In PDF format.
  2. Lecture from CMU about Mapping. Slides in PPT format.

B.4.3. Robot Path Planning and related topics.

  1. Planning-to-move.ppt Navigation and Metric Path Planning.
  2. Lecture from CMU about Path planning for mobile robots. Slides in PDF format.
  3. Paper about path planning for a mobile robot. In PDF.

B.4.4. Motion Planning and Robot Learning.

  1. New Paradigm for robot learning. In PDF.

B.4.5. Robot Obstacle Avoidance and related topics.

  1. Paper about fast obstable avoidence based on vector field histogram. In PDF.

More to be added after project assignments.
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LECTURES AND PROJECT DESCRIPTIONS BELOW THIS LINE ARE NOT MANDATORY. THEY WILL BE USED IN SOME PROJECTS ONLY.

A.2. STATIONARY ROBOTS.

A.2.1. Motion Planning for stationary robots.

  1. Motion planning methods good for stationary robot with hands. In PDF.
  2. Motion Planning that may be applied to any kind of robots. PDF.

A3. ROBOT THEATRE PROJECT


A.3.1. BASIC ROBOT THEATRE IDEAS.

  1. Towards Robot Theatre. Introduction to the class. Slides in PPT (PowerPoint). This lecture in addition reviews the basic concepts from previous robotic class. We discuss decision trees, search, automata, combinational mappings (functions), evolutionary algorithms and neural nets in robot control.
  2. Overview of AI-based robotics class. Slides in PDF.
  3. Slides on Theory of Science in PDF.

A.3.2. COMPLETE VISION-RELATED PROJECTS.

A.3.2.1. Project of student Stefan Gebauer on Speech-Vision Sonbi Robot Theatre

  1. Stefan Gebauer. Humanoid Robot based on Vision and Speech Recognition. In PDF format.
  2. Report1 from Stefan. In PDF format.
  3. Report2 from Stefan. In PDF format.
  4. Report3 from Stefan. In PDF format.
  5. Report4 from Stefan and Normen Giesecke's group. In PDF format.
  6. ZIP files for vision project.
  7. robotics2nn.zip-DEFANGED ZIP files with software and reports.

A.3.3. ROBOT SOCCER AND SIMILAR IMPROVISATIONS.

  1. Robot soccer competitions. Introduction to Robot Vision. Slides in PPT.
  2. Vision Guided Motion. Slides in PDF.
  3. Robot Soccer. Birgit Graf, student of Prof. Braunl. Here you can learn about Robot Soccer and their vision system in full detail. In PDF format.

A.5. ADVANCED PRACTICAL ALGORITHMS.

A.5.1. Matrix Calculations

  1. Fast Parallel Algorithms for Matrix problems. Slides in PPT Format.

A.7. ROBOT COMPETITIONS, ROBOT TEAMS, AND ROBOT SOCIETIES.

  1. Paper about autonomous driving mobile robot competitions. In PDF format.
  2. Technical Activities of RAS. Slides in PPT.
  3. A Probabilistic Approach to Collaborative Multi-Robot Localization. Paper in PDF.
  4. Heterogeneous Team of Modular Robots for Mapping and Exploration. Paper in PDF by Robert Grabowski.
  5. Lecture from CMU about coordination using search. In PDF format.
  6. Lecture from CMU about developing autonomy for robots in teams. Slides in PDF format This has applications to robot soccer and robot theatre.
  7. Paper about robot colony for entertainment. In PDF.

A.8. ROBOTS AND SOFTWARE OF PROFESSOR BRAUNL.

  1. 1999 paper by Prof. Braunl about the EyeBot robot Family. In PDF format.
  2. Our textbook.
  3. The Eysim Mobile Robot Simulator by Prof. Braunl. In PDF format.
  4. Client server for Eyebot. Paper in PDF.

A.9. VARIOUS ROBOTIC ARCHITECTURES.

A.9.1. Behavior Based Robotics and Biological Models.

  1. Slides in PPT about behavior based robot design. We discussed several similar ideas in class.
  2. Robots and biological intelligence. PDF.
  3. From Sensory Substitution to Situated Robots. Slides in PPT.

A.9.2. Emotional Robots.

  1. Slides in PPT by Mark Brosnan about Affective computing. This material related to class project about robot theatre.

A.9.3. Evolutionary Robots.

  1. Posters about evolutionary robotics from gecco-2002-23.pdf
  2. Introduction to robot control. Slides in PDF.
  3. Example of a world for a robot.

A.13. WALKING ROBOTS.

A.13.1. Small walking robots, especially KHR-01.

  1. Slides on Kinematics and Animation of Humanoid Robots in PPT.
  2. High Level Motion Control Slides in PPT.
  3. Modeling humanoid robots in computer graphics. Slides in PPT.
  4. Animation for computer graphics. Slides in PPT format.
  5. David Vernon. Inexpensive humanoid robot architectures. In PDF.
  6. Paper about humanoid Robots. They also use KHR-01. In PDF format.
  7. Research in Humanoid robots from Brown University. In PPT format.
  8. Random Morphology robot - Locomotion learning. One page, interesting and new. In PDF format.

A.13.2. Gaits for Walking robots

  1. Gait evolution for biped robots using visual feedback. Paper in PDF.
  2. design_walkin_gaits. Baltes et al. Design Walking gaits for small humanoid robot. In PDF format.
  3. Paper about Active Balancing using Gyroscopes for a Small Humanoid Robot. In PDF.

A.14. ROBOT HELICOPTERS AND UNDERGROUND ROBOTS.

A.14.1. Helicopters.

  1. Arducopter.

A.15. HUMAN-ROBOT AND HUMAN-COMPUTER INTERACTION.

  1. Prof. Fumio Harashima about State of the Art in Human-Computer Interaction. Much about robotics. Slides in PDF format.
  2. Lectures about Human-Robot Interaction. Slides in PDF.




BASIC SLIDES ABOUT SERVOS, SENSORS AND ROBOT VISION

A.1.2. Servos for projects.

  1. Robotic System Servo Control. Slides in PPT.

A.1.3. Sensors

  1. Sensors and their role in new approaches to perception. Slides in PPT.
  2. Digital Resistive sensors. Slides in PPT.
  3. Analog Resistive sensors. Slides in PPT.
  4. Overview of sensors. Slides in PPT.

A.1.3. Cameras and Visual Servoing

  1. Cameras. Visual Servoing. Slides in PPT.
  2. Visual Servoing for a mobile robot. Paper in PDF.
  3. Paper by Zhang on camera calibration in PDF.
  4. Camera Calibration for 3D vision. In PDF.

A.2. BASIC ROBOT VISION.


A.2.1. Edge Detection

  1. Edge detection and feature extraction algorithms. Slides in PPT.

A.2.2. Labeling and histogramming with robot applications

  1. Labeling and sequential algorithms. Slides in PPT.
  2. Histogramming. Soccer robot vision. Slides in PPT.

A.2.3. Spectral Methods in Robot Vision. Walsh and Fourier

  1. Walsh Transforms and butterflies. Slides in PPT.
  2. Walsh Matrix. Slides in PPT.
  3. Spectral Transforms and Image Processing software. Slides in PPT.
  4. Walsh and Fourier Transforms. Butterflies. Fast algorithms and their properties. Use of spectral methods in robot vision. Slides in PPT.
  5. Hough Transforms. Slides in PPT.

A.2.4. Hough Transforms and Quad Trees

  1. Hough Transform application in a mobile robot for corridor navigation. Slides in PPT.
  2. Quad trees and Oct-trees. Slides in PPT.

A.2.5. Thinning Algorithms

  1. Thinning algorithms. Slides in PPT.
  2. Review. Questions in Intelligent Robotics. In Word format. How many you can answer?
III

A.2.6. Vision for Robot Localization

  1. Vision for robot localization by Ulrich. Paper in PDF. Interesting paper.

A.2.7. Region Segmentation

  1. Region Segmentation. Slides in PDF format.

A.2.8. Wavelets

  1. Slides in PDF about wavelets.
  2. Beyond wavelets and JPEG 2000. Slides in PPT format.

A.2.9. Tracking.

  1. Lecture about Tracking Devices for humans, for instance built into glasses. In PDF format.

A.2.10. OPENCV and Examples of OPENCV Projects

  1. Thesis by Mikhail Pivtoraiko about using OpenCV on Stanton board. In Word format.
  2. Instruction about using OpenCV. In PPT format.
  3. Contact to Sam Siziliano who is OpenCV expert.
  4. Email from Anthony Kautz who build speech for robot and worked on OpenCV. Helpful. But may be obsolete now. In txt format.
  5. GOOD-NEWS-OpenCV-HBP-folks.txt
  6. cv096.dll DLL from student Jeff for project.
  7. cxcore096.dll DLL from student Jeff for project.

A.6. MATLAB AND MATLAB IN ROBOT VISION.

  1. matlab1.pdf Lectures on Matlab. Lecture 1. Introduction to Matlab.
  2. matlab2.pdf Lectures on Matlab. Lecture 2. More Matlab Programming.
  3. matlab3.pdf Lectures on Matlab. Lecture 3. Finishing with Matlab.
  4. matlab4.pdf Lectures on Matlab. Lecture 4. Finishing with Matlab.
  5. Lecture on Introduction and Control Basic to Matlab. In PDF.
  6. The same lecture in PPT.
  7. Matlab Primer in PDF.
  8. Introduction to Matlab in PPT.
  9. Matlab two-dimensional plots in PPT.
  10. Matlab Script and Function files in PPT.
  11. Simple Programming in Matlab in PPT.
  12. Solution of non-linear algebraic equations in Matlab. PPT format.
  13. F2D.mat Matlab Examples.
  14. F3D.mat F2D.mat Matlab Examples.