1. 1/22 Robot Formations Using Only Local Sensing And Control Jakob Fredslund, Maja J Mataric {jakobf, maja}@robotics.usc.edu Interaction Lab, University of Southern California, USA / Dept. of Computer Science, Aarhus University, Denmark

2. 2/22 Related Work Flocking - local info; Mataric ’95 Simulated formations – global info; Chen, Luh ’94 – local info; Desai, Ostrowski, Kumar ’01 Real robot formations – global info; Balch, Arkin ’98 – local info; Alur et al. ’00

3. 3/22 Goals Moving in formation, local info & control Arbitrary formations Formation switching Suitable for real robots (robust wrt. noise)

4. 4/22 Approach Detectable, unique IDs ID broadcast regularly (heartbeat) The conductor also broadcasts f Each robot knows: group size, IDs of all robots & the desired formation.

5. 5/22 Approach Each robot follows a friend at a certain angle and distance

6. 6/22 Approach Each robot follows a friend at a certain angle and distance Each robot has only one follower -> chain of friendships, sorted by ID.

7. 7/22 Approach Each robot follows a friend at a certain angle and distance Each robot has only one follower -> chain of friendships, sorted by ID. Median or lowest ID is conductor (centered/non-centered formations)

8. 8/22 Finding The Right Position By group size, IDs, and f, each robot knows its position in the formation ~ its friend and the angle to keep to it. N = 8, f = diamond: Self-organization gives heading

9. 9/22 The Friend-Sensor Gives friend’s ID, angle, distance Assume 180  field of view Can be panned

10. 10/22 Three Levels Of Abstraction Pan sensor Center friend in field of view Avoid collisions

11. 11/22 Implementation of Algorithm ID: color-blob detection Angle: camera pan Distance: laser Friend-sensor: camera + laser scanner Simulation/real robots (CIRA paper/tech report)

12. 12/22 Collision Avoidance Buffered bounding-box obstacle detection If robot in front: long ahead-buffer Real robot data, units are meters

13. 13/22 Pan Camera, Center Friend

14. 14/22 Experimental Evaluation Formal evaluation criteria:

15. 15/22 Properties Tested Stability of established formations Robustness to failure of group members Switching between any two formations Obstacle Avoidance ~ maintain or re- establish formation Evaluation criteria used in all experiments – results in paper.

16. 16/22 Stability Line Diamond

17. 17/22 Robustness (1) Principle: Incomplete 6-diamond to complete 4-diamond. Simulation: hexagon to pentagon.

18. 18/22 Robustness (2) Real robots: 4-wedge, 3-wedge, 4-wedge.

19. 19/22 Switching Real robots: Diamond to line.

20. 20/22 Obstacle Avoidance Real robots: two robots maintain a line while negotiating an obstacle.

21. 21/22 Conclusions Global formations from local information + minimal communication Formation guarantee (by ID) Layered algorithm -> simple rules, same for all friendship angles

22. 22/22 More Information Simulator, robot interface: http://robotics.usc.edu/player More videos & papers: http://robotics.usc.edu/~agents/projects/formations.html Thanks to Richard Vaughan, Andrew Howard, Brian Gerkey, Boyoon Jung, Esben Østergaard, & everyone in the Robotics Labs at University of Southern California, Los Angeles.