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Multi-Robot Systems: Challenges & Solutions

Explore challenges in multi-robot systems like target capture, ad-hoc networking, robot patrol, and predator-prey scenarios. Learn how different scenarios impact coordination and decision-making. Discover strategies for efficient collaboration.

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Multi-Robot Systems: Challenges & Solutions

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  1. ` • http://www.uasvision.com/2013/12/03/waterstones-trumps-amazon-with-owl-book-delivery-service/ • Also, cookies • Also, also, want to work on an app/business idea?

  2. This week: Normal lab hours. • Weekend/next week: Will email • 12/5: No class, but lab will be open • 12/8: Take-home due • 12/13: Projects due • In Class: • Presentation (20%) • Due at 8am on Angel • Write-up (60%) • Video (20%) • Code (Ungraded, but project not considered submitted without) • https://skylight.wsu.edu/student/

  3. Multi-Robot (Multi-Agent) Systems • Homogenous / Heterogeneous • Communicating / Non-Communicating • Cooperative / Competitive

  4. Multi-Robot Systems • Example 1: Target Capture • Drone finds a target • Turtlebot needs to go to the target • Why is this much harder than either of the individual tasks? • What are the risks / challenges?

  5. Risks / Challenges? • Drone’s hovering? Landing? FIRE?!? • Trust human vs. other robot • Obstacles the turtlebot can’t get around? Path planning is very different for two robots • Shared map? • Different requirements for different vehicles • Lots of data (point cloud)

  6. Multi-Robot Systems • Example 1: Target Capture • Drone finds a target • Turtlebot needs to go to the target • Why is this much harder than either of the individual tasks? • What are the risks / challenges? • What if it’s a drone and a human? How do things change? • What if it’s a human and a turtlebot?

  7. Example 2: Ad-hoc networking • Robots can communicate • 5 mobile ad-hoc network stations • Want to maximize network strength, but can only take small scale movements • How could we optimize this? • Centralized / Decentralized • Model based / free • Backtracking?

  8. Example 3: Robot Patrol • 1 robot • 2 robots • n robots

  9. Example 3: Robot Patrol • 1 robot • 2 robots • n robots

  10. Example 3: Robot Patrol • 1 robot • 2 robots • n robots • Different value targets? • Different robot capabilities? • What if could be observed?

  11. Example 3: Robot Patrol • 1 robot • 2 robots • n robots • Different value targets? • Different robot capabilities?

  12. Example 4: Hide and seek • “Hider” is stationary • Solution techniques?

  13. Example 4: Hide and seek • “Hider” is stationary • Solution techniques? • What if “hider” is learning?

  14. Example 4: Hide and seek • “Hider” is stationary • Solution techniques? • What if “hider” is learning?

  15. Example 5: Predator / Prey, without communication • 1 fixed policy prey • 4 learning predators • Need to surround the prey

  16. Example 5: Predator / Prey, with communication • 1 fixed policy prey • 4 learning predators • Need to surround the prey

  17. Example 5: Predator / Prey, with communication • 1 fixed policy prey • 4 learning predators • Need to surround the prey

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