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August 29, Overview over Systems studied in the course
 

August 29, Overview over Systems studied in the course

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Multi-Robot Systems

Multi-Robot Systems

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  • 5 min: embedded linux, embedded camera (CMU cam), lightweight arm. Version 2: notebook computer for control, webcamVersion 3: more sturdy arm, class robot. Version 4: localization system, improved mechanical design. Version 5: netbooks, local company in Denver
  • 3 min
  • 2 min

August 29, Overview over Systems studied in the course August 29, Overview over Systems studied in the course Presentation Transcript

  • Multi-Robot Systems
    CSCI 7000-006
    Friday, August 29, 2009
    NikolausCorrell
  • So far
    What is a robot and how are robot algorithms different
    Alternatives to single robot systems
    Swarms of simple, reactive individuals
    Teams of collaborative/specialized deliberative systems
    Why are multi-robot systems hard?
    Coordination
    Uncertainty
  • Today
    MRS we will study in the course
    What will we be doing in the lab?
    Components of the “Buff-Bot” (better name?)
    Project ideas
  • Topics in MRS
    Concepts
    reactive vs. deliberative algorithms
    centralized vs. distributed systems
    mixed animal-robot societies
    reconfigurable robots and smart materials
    Modeling
    Probabilistic models
    Deterministic models
    Kinematic and Dynamic Models
  • Turbine Inspection
    Goal: inspect all blades in a turbine
    Generic task allocation problem
    From reactive to deliberative algorithms
    Incremental use of resources
    Computation
    Communication
    Localization
    Degree of Planning
    Degree of Coordination
  • Multi-Robot Exploration
    Deploy into an environment
    Mapping or surveillance
    Distributed vs. Centralized algorithms
    Distributed Algorithms for Dispersion in Indoor Environments using a Swarm of Autonomous Mobile Robots”. James McLurkin and Jennifer Smith, Distributed Autonomous Robotic Systems Conference, June 23, 2004.
    Andrew Howard, Lynne E. Parker, and Gaurav S. Sukhatme. "Experiments with Large Heterogeneous Mobile Robot Team: Exploration, Mapping, Deployment and Detection". In International Journal of Robotics Research, 25(5):431-447, May 2006
  • Wifi-Deployment
    Goal: maximize area coverage of wifi signal
    Reactive algorithms
    Incremental use of resources
    Localization
    A priori information
    Swarm programming using MIT proto
    Degree of Planning
    Degree of Coordination
  • Distributed Robot Garden
    Goal: tend plants automatically
    Generic task allocation problem
    Deliberative algorithms
    Sensing and computation distributed in the environment
    Degree of Planning
    Degree of Coordination
  • Reconfigurable Systems
    Goal: reconfigure into different shapes, locomote
    Units can compress/uncompress
    Deliberative algorithms
    Vision: smart materials
    Degree of Planning
    Daniela Rus, MarsetteVona. Crystalline Robots: Self-Reconfiguration with Compressible Unit Modules. Autonomous Robots 10(1):107-124, 2001.
    Degree of Coordination
  • Smart Clay
    Goal: create arbitrary shapes on demand
    Centralized, deliberative
    Shapes are generated by unwanted parts falling off
    Process can be repeated
    Degree of Planning
    Kyle Gilpin, Keith Kotay, Daniela Rus, IuliuVasilescu - Miche: Modular Shape Formation by Self-Disassembly. The International Journal of Robotics Research 27(3-4):345-372, 2008.
    Degree of Coordination
  • Mixed Animal Robot Societies
    Not every part of the system needs to be a robot
    No direct control on animals
    How can we exploit knowledge on animal behavior for control?
  • Modeling
    How to abstract a system into a concise (mathematical model)?
    Probabilistic Models
    Population dynamics
    Discrete Event System Simulations
    Deterministic Models
    Graph-based models
    Kinematic models
    Dynamical models
  • Why a lab?
    Robotic systems are determined by their sensing, actuation, computation, and communication capabilities
    What does this mean? Find out for yourself what happens
    when information is unavailable or noisy
    when computation does not keep up with your task
    when the robot just cannot get there
    when communication does not work as you expect
    when your algorithm just does not work!
  • Developing the Buff-Bot
    Developed with students at MIT over 4 terms
    Version 5 (“Buff-Bot”): new CPU, new arm, laser
    Goal: open platform for undergraduate education
  • System Diagram: Buff Bot
    Surroundings (Lab 3)
    Localization (Lab 2)
    Vision (Lab 5)
    Sensing Computation Actuation
    Netbook (Lab 1)
    Mobile Base (Lab 2)
    Arm (Lab 4)
  • Lab Syllabus
    Building a teaching and research platform “Buff-Bot”
    Part 1: Robotic Operating System
    Part 2: Differential wheel base and localization
    Part 3: Mapping with the LMS
    Part 4: Arm
    Part 5: Vision
  • Project
    Inspired by the systems and models presented in the course and/or your work
    Using the Buff-Bot, additional hardware or simulation
    Working with other teams on common components and tools
  • Art Gallery Problem
    What about robots watching an area and sending a guard when something happens?
    How long does it take until an event is detected? Responded?
  • Distributed Robot Garden
    Sensors on the plants vs. sensors on the robots
    What is better, faster, cheaper?
    Centralized vs. Decentralized coordination: when does it make sense to distribute?
  • Smart Building Blocks
    What about a construction kit in which the parts always take the shape you need?
    What parts do you need to create specific objects/trusses?
    Which part takes which shape?
  • Smart Marbles
    What about a set of marbles that you fill into a cavity and learn about its inside?
    How can you reconstruct the topology of the cavity?
    What sensing, computation, and communication capabilities does each marble need?
  • Smart Rubber
    What about rubber that can change its shape and move forwards?
    How to model structures made only of soft elements?
    What else can we build?
  • Summary
    Multi Robot Systems range from robot teams to smart materials composed of hundreds of sensing, actuated, computational and communicating devices
    Be creative in your course project, now is the time
  • Next Week
    Monday: Reactive Algorithms I
    Wednesday: Reactive Algorithms II, Practice: Robot architectures and operating systems
    Friday: Lab 1