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Advanced Topics in Robotics CS493/790 (X) Lecture 1 Instructor: Monica Nicolescu General Information • Instructor: Dr. Monica Nicolescu – E-mail: [email protected] – Office hours: Tuesday, Thursday; 11:00am-noon – Room: SEM 239 • Class webpage: – http://www.cs.unr.edu/~monica/Courses/CS493-790/ • Lectures – Tuesday: 9:30-10:45am SEM 344 • Laboratory – Thursday: 9:30-10:45am SEM 246 CS 493/790(X) - Lecture 1 2 What will we Learn? • Cover fundamental aspects of robotics – What is a robot? – Robot control architectures • Advanced robotics techniques – Biologically inspired robotics – Robot learning: reinforcement, imitation, demonstration, genetic algorithms – Multiple robot systems: coordination and cooperation – Human-robot interaction – Navigation and mapping • Hands-on experience CS 493/790(X) - Lecture 1 3 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 CS 493/790(X) - Lecture 1 4 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 CS 493/790(X) - Lecture 1 5 Project/Lab 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 Playercompatible physical robots. CS 493/790(X) - Lecture 1 6 Project/Lab Testbeds • One Player-compatible ActivMedia Pioneer 3 DX – sonar sensors – Laser – PTZ camera – Onboard computer • One Player-compatible ActivMedia Pioneer 1 AT robot – 7 sonar sensors and requires the use of a laptop (not provided) • 16 LEGO robot kits – Handy Board microcontroller – Programming in Interactive C CS 493/790(X) - Lecture 1 7 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) CS 493/790(X) - Lecture 1 8 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 – Discussion (strengths and weaknesses) and conclusion – References – Appendix (relevant code or algorithms) CS 493/790(X) - Lecture 1 9 Class Policy • Grading – Paper reports: 15% – Paper presentations: 20% – Participation in class discussions: 15% – Lab assignments: 20% – Final project: 30% • Late submissions – No late submissions will be accepted • Attendance – Full participation in class discussions CS 493/790(X) - Lecture 1 10 Important Dates/Milestones • February 23 – Project topic proposal and presentation – One page that outlines the specific goals, contribution, implementation platform and the proposed approach • April 6 – 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 CS 493/790(X) - Lecture 1 11 Important Dates/Milestones • May 12 – Project final presentations – Project final demonstrations – Project final reports due CS 493/790(X) - Lecture 1 12 Optional Textbooks • Basic topics – The Robotics Primer, 2001. Author: Maja Mataric' – Available in draft form at the bookstore • Advanced topics – Behavior-Based Robotics, 2001. Author: Ron Arkin – Available at the library • Lego Robots – Robotic Explorations: An Introduction to Engineering Through Design, 2001. Author: Fred G. Martin CS 493/790(X) - Lecture 1 13 Key Concepts • Situatedness – Agents are strongly affected by the environment and deal with its immediate demands (not its abstract models) directly • Embodiment – Agents have bodies, are strongly constrained by those bodies, and experience the world through those bodies, which have a dynamic with the environment CS 493/790(X) - Lecture 1 14 Key Concepts (cont.) • Situated intelligence – is an observed property, not necessarily internal to the agent or to a reasoning engine; instead it results from the dynamics of interaction of the agent and environment – and behavior are the result of many interactions within the system and w/ the environment, no central source or attribution is possible CS 493/790(X) - Lecture 1 15 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 CS 493/790(X) - Lecture 1 16 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 • Robot = an autonomous system which exists in the physical world, can sense its environment and can act on it to achieve some goals CS 493/790(X) - Lecture 1 17 Challenges • Perception – Limited, noisy sensors • Actuation – Limited capabilities of robot effectors • Thinking – Time consuming in large state spaces • Environments – Dynamic, impose fast reaction times CS 493/790(X) - Lecture 1 18 Uncertainty • Uncertainty is a key property of existence in the physical world • Physical sensors provide limited, noisy, and inaccurate information • Physical effectors produce limited, noisy, and inaccurate action • The uncertainty of physical sensors and effectors is not well characterized, so robots have no available a priori models CS 493/790(X) - Lecture 1 19 Uncertainty (cont.) • A robot cannot accurately know the answers to the following: – Where am I? – Where are my body parts, are they working, what are they doing? – What did I just do? – What will happen if I do X? – Who/what are you, where are you, what are you doing, etc.?... CS 493/790(X) - Lecture 1 20 Classical activity decomposition • Locomotion (moving around, going places) – factory delivery, Mars Pathfinder, lawnmowers, vacuum cleaners... • Manipulation (handling objects) – factory automation, automated surgery... • This divides robotics into two basic areas – mobile robotics – manipulator robotics • … but these are merging in domains like robot pets, robot soccer, and humanoids CS 493/790(X) - Lecture 1 21 Robots: Alternative Terms • UAV – unmanned aerial vehicle • UGV (rover) – unmanned ground vehicle • UUV – unmanned undersea vehicle CS 493/790(X) - Lecture 1 22 An assortment of robots… CS 493/790(X) - Lecture 1 23 Anthropomorphic Robots CS 493/790(X) - Lecture 1 24 Animal-like Robots CS 493/790(X) - Lecture 1 25 Humanoid Robots QRIO Asimo (Honda) Robonaut (NASA) CS 493/790(X) - Lecture 1 DB (ATR) Sony Dream Robot 26 A Brief History of Robotics • Robotics grew out of the fields of control theory, cybernetics and AI • Robotics, in the modern sense, can be considered to have started around the time of cybernetics (1940s) • Early AI had a strong impact on how it evolved (1950s-1970s), emphasizing reasoning and abstraction, removal from direct situatedness and embodiment • In the 1980s a new set of methods was introduced and robots were put back into the physical world CS 493/790(X) - Lecture 1 27 W. Grey Walter’s Tortoise • Machina Speculatrix” (1953) – 1 photocell, 1 bump sensor, 1 motor, 3 wheels, 1 battery • Behaviors: – seek light – head toward moderate light – back from bright light – turn and push – recharge battery • Uses reactive control, with behavior prioritization CS 493/790(X) - Lecture 1 28 Braitenberg Vehicles • Valentino Braitenberg (1980) • Thought experiments – Use direct coupling between sensors and motors – Simple robots (“vehicles”) produce complex behaviors that appear very animal, life-like • Excitatory connection – The stronger the sensory input, the stronger the motor output – Light sensor wheel: photophilic robot (loves the light) • Inhibitory connection – The stronger the sensory input, the weaker the motor output – Light sensor wheel: photophobic robot (afraid of the light) CS 493/790(X) - Lecture 1 29 Example Vehicles • Wide range of vehicles can be designed, by changing the connections and their strength Vehicle 1 • Vehicle 1: Being “ALIVE” – One motor, one sensor • Vehicle 2: “FEAR” and “AGGRESSION” – Two motors, two sensors Vehicle 2 – Excitatory connections • Vehicle 3: “LOVE” – Two motors, two sensors – Inhibitory connections CS 493/790(X) - Lecture 1 30 Artificial Intelligence • Officially born in 1956 at Dartmouth University – Marvin Minsky, John McCarthy, Herbert Simon • Intelligence in machines – Internal models of the world – Search through possible solutions – Plan to solve problems – Symbolic representation of information – Hierarchical system organization – Sequential program execution CS 493/790(X) - Lecture 1 31 AI and Robotics • AI influence to robotics: – Knowledge and knowledge representation are central to intelligence • Perception and action are more central to robotics • New solutions developed: behavior-based systems – “Planning is just a way of avoiding figuring out what to do next” (Rodney Brooks, 1987) • Distributed AI (DAI) – Society of Mind (Marvin Minsky, 1986): simple, multiple agents can generate highly complex intelligence • First robots were mostly influenced by AI (deliberative) CS 493/790(X) - Lecture 1 32 Background Readings • F. Martin: Sections 1.1, 1.2.3 • M. Matarić: Chapters 1, 3 CS 493/790(X) - Lecture 1 33