Multi-Robot Systems

1. Multi-Robot Systems CSCI 7000-006 Friday, August 29, 2009 NikolausCorrell

2. 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

3. 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

4. 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

5. 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

6. 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

7. 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

8. 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

9. 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

10. 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

11. 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?

12. 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

13. 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!

14. 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

15. 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)

16. 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

17. 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

18. 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?

19. 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?

20. 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?

21. 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?

22. 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?

23. 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

24. Next Week Monday: Reactive Algorithms I Wednesday: Reactive Algorithms II, Practice: Robot architectures and operating systems Friday: Lab 1