1. Advanced Topics in Robotics CS493/790 (X) Lecture 1 Instructor: Monica Nicolescu

2. CS 493/790(X) - Lecture 12 What will we Learn? Cover fundamental aspects of robotics –What is a robot? –What are robots composed of? –How do we control/program robots? Advanced robotics techniques –Development of the robotics field and the main directions of research in this area –Representative approaches to robot control, learning, coordination and cooperation between multiple robots and human-robot interaction Hands-on experience

3. CS 493/790(X) - Lecture 13 General Information Instructor: Dr. Monica Nicolescu –E-mail: monica@cs.unr.edu –Office hours: Tuesday, Thursday 2:30pm-3:30pm –Room: SEM 239 Class webpage: –http://www.cs.unr.edu/~monica/Courses/CS493-790/ Time and Place –Tuesday: 9:30-10:45am; PE 205 Laboratory room –SEM 246

4. CS 493/790(X) - Lecture 14 Readings and Presentations Two papers (on average) discussed at each lecture Each paper is presented by a student Presentation guidelines –At most 30 minutes –Briefly summarize the paper –Discuss the paper, its strengths, weaknesses, any points needing clarification –Addressing any questions the other students may have

5. CS 493/790(X) - Lecture 15 Readings and Paper Reports For each paper, all students must submit, at the beginning of the class a brief report of the paper Report format (typed) –Student's name –Title and authors of the paper –A short paragraph summarizing the contributions of the paper –A critique of the paper that addresses the strengths and weaknesses of the paper

6. CS 493/790(X) - Lecture 16 Project Individual project on topics covered in class Project topics: an implementation of either: –a single robot system (involving complex behavior and demonstrated on a physical robot) or –a multi-robot system (involving cooperation/ communication/ coordination between robots and demonstrated in simulation)

7. CS 493/790(X) - Lecture 17 Project Reports Should include the following: –Title, author –Abstract –Introduction and motivation –Problem definition: project goals, assumptions, constraints, and evaluation criteria –Details of proposed approach –Results and objective experimental evaluation –Review of relevant literature and previous research and how it relates to the project –Discussion (strengths and weaknesses) and conclusion –References –Appendix (relevant code or algorithms)

8. CS 493/790(X) - Lecture 18 Project Testbeds The Player-Stage-Gazebo simulator (playerstage.sourceforge.net) –Player is a general purpose language-indepedent network server for robot control –Stage is a Player-compatible high-fidelity indoor multi-robot simulation testbed –Gazebo is a Player-compatible high-fidelity 3D outdoor simulation testbed with dynamics –Player/Stage/Gazebo allows for direct porting to Player- compatible physical robots.

9. CS 493/790(X) - Lecture 19 Project Testbeds One Player-compatible ActivMedia Pioneer 1 AT (all terrain) robot –7 sonar sensors and requires the use of a laptop (not provided) One Player-compatible ActivMedia Pioneer 1 indoor robot –7 sonar sensors and requires the use of a laptop (not provided) 16 LEGO robot kits –Handy Board microcontroller –Programming in Interactive C

10. CS 493/790(X) - Lecture 110 Class Policy Grading –Paper reports: 20% –Participation in class discussions: 20% –Paper presentations: 20% –Final project: 40% Late submissions –No late submissions will be accepted Attendance –Full participation in class discussions

11. CS 493/790(X) - Lecture 111 Important Dates/Milestones September 21 –Project topic proposal and presentation –One page that outlines the specific goals, implementation platform and the proposed approach November 4 –Project status presentations –5 minute in-class presentation –One-two pages that describe the current status of the project, what has been done, what is still to be done

12. CS 493/790(X) - Lecture 112 Important Dates/Milestones December 7 –Project final presentations –May extend to Dec 2&7 December 10 –Project final demonstrations –Project final reports due

13. CS 493/790(X) - Lecture 113 Optional Textbooks Basic topics –The Robotics Primer, 2001. Author: Maja Mataric' –Will be available in draft form at the bookstore Advanced topics –Behavior-Based Robotics, 2001. Author: Ron Arkin –Available at the library

14. CS 493/790(X) - Lecture 114 Optional Textbooks Lego Robots –Robotic Explorations: An Introduction to Engineering Through Design, 2001. Author: Fred G. Martin

15. CS 493/790(X) - Lecture 115 The term “robot” Karel Capek’s 1921 play RUR (Rossum’s Universal Robots) –It is (most likely) a combination of “rabota” (obligatory work) and “robotnik” (serf) Most real-world robots today do perform such “obligatory work” in highly controlled environments –Factory automation (car assembly) But that is not what robotics research about; the trends and the future look much more interesting

16. CS 493/790(X) - Lecture 116 What is a Robot? In the past –A clever mechanical device – automaton Robotics Industry Association, 1985 –“A re-programmable, multi-functional manipulator designed to move material, parts, tools, or specialized devices […] for the performance of various tasks” What does this definition missing? –Notions of thought, reasoning, problem solving, emotion, consciousness

17. CS 493/790(X) - Lecture 117 A Robot is… … a machine able to extract information from its environment and use knowledge about its world to act safely in a meaningful and purposeful manner (Ron Arkin, 1998) … an autonomous system which exists in the physical world, can sense its environment and can act on it to achieve some goals

18. CS 493/790(X) - Lecture 118 What is Robotics? Robotics is the study of robots, autonomous embodied systems interacting with the physical world Robotics addresses perception, interaction and action, in the physical world

19. CS 493/790(X) - Lecture 119 Robots: Alternative Terms UAV –unmanned aerial vehicle UGV (rover) –unmanned ground vehicle UUV –unmanned undersea vehicle

20. CS 493/790(X) - Lecture 120 An assortment of robots…

21. CS 493/790(X) - Lecture 121 Anthropomorphic Robots

22. CS 493/790(X) - Lecture 122 Animal-like Robots

23. CS 493/790(X) - Lecture 123 More Robots Maron-1: Fujitsu Robovie-M: VStone

24. CS 493/790(X) - Lecture 124 Humanoid Robots Robonaut (NASA)Sony Dream Robot Asimo (Honda) DB (ATR) QRIO

25. CS 493/790(X) - Lecture 125 What is in a Robot? Sensors Effectors and actuators –Used for locomotion and manipulation Controllers for the above systems –Coordinating information from sensors with commands for the robot’s actuators

26. CS 493/790(X) - Lecture 126 Sensors Sensor = physical device that provides information about the world –Process is called sensing or perception What does a robot need to sense? –Depends on the task it has to do Sensor (perceptual) space –All possible values of sensor readings –One needs to “see” the world through the robot’s “eyes” –Grows quickly as you add more sensors

27. CS 493/790(X) - Lecture 127 State State: A description of the robot (of a system in general) For a robot state can be: –Observable: the robot knows its state entirely –Partially observable: the robot only knows a part of its state –Hidden (unobservable): the robot does not have any access to its state –Discrete: up, down, blue, red –Continuous: 2.34 mph

28. CS 493/790(X) - Lecture 128 Types of State External –The state of the world as perceived by the robot –Perceived through sensors –E.g.: sunny, cold Internal –The state of the robot as it can perceive it –Perceived through internal sensors, monitoring (stored, remembered state) –E.g.: Low battery, velocity The robot’s state is the combination of its internal and external state

29. CS 493/790(X) - Lecture 129 State Space All possible states a robot could be in –E.g.: light switch has two states, ON, OFF; light switch with dimmer has continuous state (possibly infinitely many states) Different than the sensor/perceptual space!! –Internal state may be used to store information about the world (maps, location of “food”, etc.) How intelligent a robot appears is strongly dependent on how much and how fast it can sense its environment and about itself

30. CS 493/790(X) - Lecture 130 Representation Internal state that stores information about the world is called a representation or internal model –Self: stored proprioception, goals, intentions, plans –Environment: maps –Objects, people, other robots –Task: what needs to be done, when, in what order Representations and models influence determine the complexity of a robot’s “brain”

31. CS 493/790(X) - Lecture 131 Action Effectors: devices of the robot that have impact on the environment (legs, wings  robotic legs, propeller) Actuators: mechanisms that allow the effectors to do their work (muscles  motors) Robotic actuators are used for –locomotion (moving around, going places) –manipulation (handling objects) This divides robotics into two basic areas –Mobile robotics –Manipulator robotics

32. CS 493/790(X) - Lecture 132 Autonomy Autonomy is the ability to make one’s own decisions and act on them. –For robots: take the appropriate action on a given situation Autonomy can be complete (R2D2) or partial (teleoperated robots) Controllers enable robots to be autonomous –Play the role of the “brain” and nervous system in animals –Typically more than one controller, each process information from sensors and decide what actions to take –Challenge in robotics: how do all these controllers coordinate with each other?

33. CS 493/790(X) - Lecture 133 Control Architectures Robot control is the means by which the sensing and action of a robot are coordinated Control architecture –Guiding principles and constraints for organizing a robot’s control system Robot control may be implemented: –In hardware: programmable logic arrays –In software Controllers need not (should not) be a single program –Should control modules be centralized?

34. CS 493/790(X) - Lecture 134 Languages for Programming Robots What is the best robot programming language? –There is no “best” language In general, use the language that – Is best suited for the task –Comes with the hardware –You are used to General purpose: –JAVA, C Specially designed: –the Behavior Language, the Subsumption Language

35. CS 493/790(X) - Lecture 135 Background Readings F. Martin: Sections 1.1, 1.2.3 M. Matarić: Chapters 1, 3