Multi-Robot Systems<br />CSCI 7000-006<br />Wednesday, August 27, 2009<br />NikolausCorrell<br />
Last lecture<br />Highlights from<br />mechanisms<br />control<br />algorithms<br />coordination<br />Multi-robot system K...
Last Lecture<br />Possible algorithms are a function of available<br />Sensing<br />Computation<br />Communication<br />Me...
Today<br />Why Multi-Robot Systems?<br />Planning and Coordination<br />Reactive vs. Deliberative Algorithms<br />
Course Question<br />When and why would it make sense to actually use more than one robot?<br />
Why Multi-Robot Systems?<br />Robustness<br />“If one robot fails, the others step in”<br />Scalability<br />“If the probl...
Reactive Coordination: Shortest path routing in ant colonies<br />Task: find shortest path<br />Ants choose bridge probabi...
Analysis<br />Sensing: pheromone level<br />Computation: biased random number generator (or just noise when reading pherom...
Course Questions<br />Come up with “better” algorithms for solving the problem using a robot swarm. What capabilities woul...
Alternative 1: Fully planned, tightly coordinated<br />3<br />1<br />Let’s take the north branch!<br />I arrived via North...
 Concept “Shortest Path”
 Reliable Execution</li></ul>South<br />
Alternative 2: Single robot<br />G<br />S<br />
Lessons learned from the ants<br />Robustness<br />Unreliable team members<br />Misreading of the pheromone trail<br />Sca...
Deliberative Coordination: Yacht Racing<br />
System architecture<br />Weather<br />Sails<br />Grinders<br />Strategist<br />Navigator<br />Helmsman<br />Tactician<br /...
Analysis<br />Sensing:weather, competition, landmarks<br />Computation: optimal policies for heading, sails and trim<br />...
Lessons from yachting example<br />Robustness<br />Not robust to communication and material failures<br />Scalability<br /...
Course question<br />Could the boat be run by a single person?<br />
Multi-Robot vs. Single Robot Systems<br />Each multi-robot system can be replaced by a single robot<br />The real question...
Course Question<br />Look at the diagram<br />Where would you position the ants?<br />Where would you position the yacht c...
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August 27, Introduction to Multi-Robot Systems

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Multi-Robot Systems

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  • 10 min: goal: deliberative vs. randomized, centralized vs. decentralized, relation between algorithms and capabilities
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  • 10 min: goal: deliberative vs. randomized, centralized vs. decentralized, relation between algorithms and capabilities
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  • August 27, Introduction to Multi-Robot Systems

    1. 1. Multi-Robot Systems<br />CSCI 7000-006<br />Wednesday, August 27, 2009<br />NikolausCorrell<br />
    2. 2. Last lecture<br />Highlights from<br />mechanisms<br />control<br />algorithms<br />coordination<br />Multi-robot system Kiva<br />Centralized control<br />Task allocation on grid environment<br />
    3. 3. Last Lecture<br />Possible algorithms are a function of available<br />Sensing<br />Computation<br />Communication<br />Mechanism<br />
    4. 4. Today<br />Why Multi-Robot Systems?<br />Planning and Coordination<br />Reactive vs. Deliberative Algorithms<br />
    5. 5. Course Question<br />When and why would it make sense to actually use more than one robot?<br />
    6. 6. Why Multi-Robot Systems?<br />Robustness<br />“If one robot fails, the others step in”<br />Scalability<br />“If the problem gets bigger, just get more robots”<br />Performance<br />“More robots will get this done faster”<br />Specialization<br />“While some robots do this, others do already that”<br />
    7. 7. Reactive Coordination: Shortest path routing in ant colonies<br />Task: find shortest path<br />Ants choose bridge probabilistically<br />Ants leave pheromone trace<br />Probability function of pheromone level<br />Pheromones evaporate eventually<br />Jean-Louis Deneubourg, ULB<br />
    8. 8. Analysis<br />Sensing: pheromone level<br />Computation: biased random number generator (or just noise when reading pheromones?)<br />Actuation:biased random walk<br />Communication: indirect<br />
    9. 9. Course Questions<br />Come up with “better” algorithms for solving the problem using a robot swarm. What capabilities would the robots need for your solution?<br />Come up with an algorithm that requires a single robot. What sensors does it need?<br />
    10. 10. Alternative 1: Fully planned, tightly coordinated<br />3<br />1<br />Let’s take the north branch!<br />I arrived via North<br />North<br />2<br />I’m not there yet!<br />http://www.myrmecos.net/<br />Requires<br /><ul><li> Communication
    11. 11. Concept “Shortest Path”
    12. 12. Reliable Execution</li></ul>South<br />
    13. 13. Alternative 2: Single robot<br />G<br />S<br />
    14. 14. Lessons learned from the ants<br />Robustness<br />Unreliable team members<br />Misreading of the pheromone trail<br />Scalability<br />Yes, due to decentralized, distributed coordination<br />Performance<br />Probabilistic completeness<br />Specialization<br />Not in this example (more on ants later)<br />Good performance despite limited sensing, computation, and communication<br />
    15. 15. Deliberative Coordination: Yacht Racing<br />
    16. 16. System architecture<br />Weather<br />Sails<br />Grinders<br />Strategist<br />Navigator<br />Helmsman<br />Tactician<br />Runner<br />Trim<br />Communication<br />Competition<br />Trimmers<br />Sensing<br />Landmarks/Position<br />Computation<br />Actuation<br />
    17. 17. Analysis<br />Sensing:weather, competition, landmarks<br />Computation: optimal policies for heading, sails and trim<br />Actuation:heading, sails and trim<br />Communication: voice and gestures, potentially lossy<br />
    18. 18. Lessons from yachting example<br />Robustness<br />Not robust to communication and material failures<br />Scalability<br />Limited due to hierarchical, centralized architecture<br />Performance<br />Optimal given optimal sensing, communication and actuation<br />Specialization<br />high<br />Fortune favors the bold: “Best” policies yield close to optimal performance under uncertainty.<br />
    19. 19. Course question<br />Could the boat be run by a single person?<br />
    20. 20. Multi-Robot vs. Single Robot Systems<br />Each multi-robot system can be replaced by a single robot<br />The real question is: what is feasible?<br />The number of robots to solve a given task is a resource trade-off problem:<br />Few more capable units vs. many simple ones<br />What are the constraints on time/cost/size to solve the problem<br />…<br />
    21. 21. Course Question<br />Look at the diagram<br />Where would you position the ants?<br />Where would you position the yacht crew?<br />Degree of Planning<br />Degree of Coordination<br />
    22. 22. Summary<br />A multi-robot system is determined by the distribution of <br />Sensing<br />Computation<br />Actuation <br />Communication<br />A coordination algorithm is a best-effort approach based on these capabilities<br />Best possible planning<br />Best possible coordination<br />Capabilities are almost always probabilistic and make coordination a hard problem<br />
    23. 23. Next Lectures<br />Friday: Components of the Buff-Bot<br />Next week<br />Lecture: a case study in multi-robot inspection<br />Practice: robotic operating systems<br />Lab: getting started with ROS<br />

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