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

CS 493/790(X) - Lecture 12 General Information Instructor: Dr. Monica Nicolescu – –Office hours: Tuesday, Thursday; 11:00am-noon –Room: SEM 239 Class webpage: – Lectures –Tuesday: 9:30-10:45am SEM 344 Laboratory –Thursday: 9:30-10:45am SEM 246

CS 493/790(X) - Lecture 13 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 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

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

CS 493/790(X) - Lecture 16 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 Player- compatible physical robots.

CS 493/790(X) - Lecture 17 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 18 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 19 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 110 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 111 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 112 Important Dates/Milestones May 12 –Project final presentations –Project final demonstrations –Project final reports due

CS 493/790(X) - Lecture 113 Optional Textbooks Basic topics –The Robotics Primer, Author: Maja Mataric' –Available in draft form at the bookstore Advanced topics –Behavior-Based Robotics, Author: Ron Arkin –Available at the library Lego Robots –Robotic Explorations: An Introduction to Engineering Through Design, Author: Fred G. Martin

CS 493/790(X) - Lecture 114 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 115 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 116 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 117 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 118 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 119 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 120 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 121 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 122 Robots: Alternative Terms UAV –unmanned aerial vehicle UGV (rover) –unmanned ground vehicle UUV –unmanned undersea vehicle

CS 493/790(X) - Lecture 123 An assortment of robots…

CS 493/790(X) - Lecture 124 Anthropomorphic Robots

CS 493/790(X) - Lecture 125 Animal-like Robots

CS 493/790(X) - Lecture 126 Humanoid Robots Robonaut (NASA)Sony Dream Robot Asimo (Honda) DB (ATR) QRIO

CS 493/790(X) - Lecture 127 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 128 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 129 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 130 Example Vehicles Wide range of vehicles can be designed, by changing the connections and their strength Vehicle 1: –One motor, one sensor Vehicle 2: –Two motors, two sensors –Excitatory connections Vehicle 3: –Two motors, two sensors –Inhibitory connections Being “ALIVE” “FEAR” and “AGGRESSION” “LOVE” Vehicle 1 Vehicle 2

CS 493/790(X) - Lecture 131 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 132 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 133 Background Readings F. Martin: Sections 1.1, M. Matarić: Chapters 1, 3