Topics: Introduction to RoboticsCS 491/691(X): Topics: Introduction to Robotics CS 491/691(X) Lecture 1 Instructor: Monica Nicolescu


General Information: General Information Instructor: Dr. Monica Nicolescu E-mail: monica@cs.unr.edu Office hours: Tuesday, Thursday 10:30am-12:00pm Room: SEM 239 Class webpage: http://www.cs.unr.edu/~monica/Courses/CS491-691/


Time and Place: Time and Place Lectures Tuesday: 1:00pm-2:15pm, SFB 103 Labs Thursday: 1:00pm-2:15pm, SEM 342A The use of the lab equipment requires a $50 deposit paid at the cashier’s office Deposit is returned at the end of the semester


Class Policy: Class Policy Grading Homeworks: 20% Exam (1): 20% Exam (2): 20% Laboratory sessions: 20% Final project: 20% Late submissions No late submissions will be accepted Attendance Exams, laboratory sessions and final competition are mandatory If you cannot attend you must discuss with the instructor in advance


Textbooks: Textbooks Lectures The Robotics Primer, 2001. Author: Maja Mataric' Available in draft form at the bookstore Labs Robotic Explorations: An Introduction to Engineering Through Design, 2001. Author: Fred G. Martin


What will we Learn?: What will we Learn? Fundamental aspects of robotics What is a robot? What are robots composed of? How do we control/program robots? Hands-on experience Build robots using LEGO parts Control robots using Interactive C and the HandyBoard microcontroller Contests during the semester, final competition


The term “robot”: 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


What is a Robot?: 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


A Robot is…: 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


What is Robotics?: 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


Robots: Alternative Terms: Robots: Alternative Terms UAV unmanned aerial vehicle UGV (rover) unmanned ground vehicle UUV unmanned undersea vehicle


An assortment of robots…: An assortment of robots…


Anthropomorphic Robots: Anthropomorphic Robots


Animal-like Robots: Animal-like Robots


Humanoid Robots: Humanoid Robots Robonaut (NASA) Sony Dream Robot Asimo (Honda) DB (ATR) QRIO


What is in a Robot?: 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


Sensors: 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


State: 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


Types of State: 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


State Space: 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


Representation: 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”


Action: 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


Autonomy: 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?


Control Architectures: 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?


Languages for Programming Robots: 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


Spectrum of robot control: Spectrum of robot control From “Behavior-Based Robotics” by R. Arkin, MIT Press, 1998


Robot control approaches: Robot control approaches Reactive Control Don’t think, (re)act. Deliberative (Planner-based) Control Think hard, act later. Hybrid Control Think and act separately & concurrently. Behavior-Based Control (BBC) Think the way you act.


Thinking vs. Acting: Thinking vs. Acting Thinking/Deliberating slow, speed decreases with complexity involves planning (looking into the future) to avoid bad solutions thinking too long may be dangerous requires (a lot of) accurate information flexible for increasing complexity Acting/Reaction fast, regardless of complexity innate/built-in or learned (from looking into the past) limited flexibility for increasing complexity


How to Choose a Control Architecture?: How to Choose a Control Architecture? For any robot, task, or environment consider: Is there a lot of sensor noise? Does the environment change or is static? Can the robot sense all that it needs? How quickly should the robot sense or act? Should the robot remember the past to get the job done? Should the robot look ahead to get the job done? Does the robot need to improve its behavior and be able to learn new things?


Reactive Control: Don’t think, react!: Reactive Control: Don’t think, react! Technique for tightly coupling perception and action to provide fast responses to changing, unstructured environments Collection of stimulus-response rules Limitations No/minimal state No memory No internal representations of the world Unable to plan ahead Unable to learn Advantages Very fast and reactive Powerful method: animals are largely reactive


Deliberative Control: Think hard, then act!: Deliberative Control: Think hard, then act! In DC the robot uses all the available sensory information and stored internal knowledge to create a plan of action: sense  plan  act (SPA) paradigm Limitations Planning requires search through potentially all possible plans  these take a long time Requires a world model, which may become outdated Too slow for real-time response Advantages Capable of learning and prediction Finds strategic solutions


Readings: Readings F. Martin: Sections 1.1, 1.2.3 M. Matarić: Chapters 1, 3