The TeamBots Environment

1. The TeamBots Environment Tucker Balch The Borg Lab Georgia Institute of Technology

2. Why TeamBots? Why “Environment?” • Robotics researchers need more than a language, we need a flexible, manageable environment that provides: • Consistent APIs to robot hardware • Simulation • Communication • Graphical tools • Code reuse Tucker Balch Georgia Institute of Technology

3. What is TeamBots? • TeamBots is a Java-based collection of applications and libraries designed to support robotics research: • TBSim: configurable simulation tool • TBHard: robot executive • RoboComm: communications package • Clay: library for programming behavior-based controllers (maybe Clay is an architecture) Tucker Balch Georgia Institute of Technology

4. Robot Controller API Simulation Hardware TeamBots Software Architecture: Design Tucker Balch Georgia Institute of Technology

5. Java: The Good • Syntax supports layered control system configuration (more on that later) • Rich set of libraries (threads, GUI tools, communications) • Portable • Automated documentation • Hard to shoot yourself in the foot • Strongly typed • Object oriented • No pointers Tucker Balch Georgia Institute of Technology

6. Java: The Bad • Religion & Hype • Java is slow • Timing is unpredictable due to GC • Work arounds: • Speed: • Use JITs, native compilers • GC • GC at regular intervals • 10% to 20% performance hit er Tucker Balch Georgia Institute of Technology

7. Robot Controller API Simulation Example TeamBots Simulations • RoboCup small size soccer • Nomad 150 • Probotics Cye vehicle • Outdoor vehicles Tucker Balch Georgia Institute of Technology

8. How TBSim Works • Read in and parse description file: • Two types of objects • Objects without control systems • Objects with control systems (robots) • For each object: object.init() • For each control system: cs.init() • While not done • For each object: object.takeStep() • For each control system: cs.takeStep() Tucker Balch Georgia Institute of Technology

9. simulated obstacle simulated robot hardware simulated obstacle simulated obstacle simulated obstacle Robot 1 Control System simulated robot hardware Robot 2 Control System TBSim Implementation Control Systems Simulated World Tucker Balch Georgia Institute of Technology

10. Description File Syntax bounds –5 5 5 –5 // meters timestep 100 // milliseconds timeout 60000 // milliseconds trials 10 graphics on seed 993 windowsize 500 500 // pixels object Obstacle 0 4 0 1 x0000FF x000000 4 robot Nomad150 forage 0 1 0 x000000 xFF0000 2 Tucker Balch Georgia Institute of Technology

11. Robot Controller API Hardware TeamBots Hardware Support • Nomad 150 (Balch & Arkin, Georgia Tech) • ISR Pebbles (Ram, Georgia Tech) • Probotics’ Cye (Balch & Veloso, CMU) • Amigobot (Luke, UMD) • RWI ATRV (Koenig & Balch, Georgia Tech) Tucker Balch Georgia Institute of Technology

12. TBHard java TBHard Nomad150 forage desoto.cc.gatech.edu 3 600 0 0 0 Tucker Balch Georgia Institute of Technology

13. Nomad 150 • Balch, AI Magazine, 1997. • Balch, Autonomous Robots, 2000. Tucker Balch Georgia Institute of Technology

14. Nomad 150 • Balch, AI Magazine, 1997. • Balch, Autonomous Robots, 2000. Tucker Balch Georgia Institute of Technology

15. Nomad 150 • Balch, AI Magazine, 1997. • Balch, Autonomous Robots, 2000. Tucker Balch Georgia Institute of Technology

16. Nomad 150 • Balch, AI Magazine, 1997. • Balch, Autonomous Robots, 2000. Tucker Balch Georgia Institute of Technology

17. Probotics’ Cye Tucker Balch Georgia Institute of Technology

18. Robot Controller API Simulation Hardware How Robot APIs are Defined • Make use of Java features • Inheritance • Interfaces Tucker Balch Georgia Institute of Technology

19. Simple implements implements Nomad150 Nomad150Comm Nomad150CommSim Nomad150Hard Nomad150Sim Nomad150CommHard implements implements Robot API Hierarchy: Design extends extends Tucker Balch Georgia Institute of Technology

20. Robot API Hierarchy: Code public interface Nomad150Comm extends Nomad150, Transciever {} public class Nomad150CommSim extends Nomad150Sim implements Nomad150Comm, SimulatedObject {} Tucker Balch Georgia Institute of Technology

21. Inter-Robot Communication: RoboComm • Simple API to TCP/IP • Unicast • Broadcast • Multicast • Implemented in simulation and on mobile robots • Uses Java serialization for marshaling and unmarshaling Tucker Balch Georgia Institute of Technology

22. Inter-Robot Communication t.unicast(2, new stringMessage( "hello!")); if (r.hasMoreElements()) new_message = r.getNextElement(); Tucker Balch Georgia Institute of Technology

23. Clay: An Architecture for Robot Control • Uses features of Java syntax to embed perceptual processes within action and selection processes • Allows specification of flexible hierarchies • Run time execution is efficient because only the necessary portions of the configuration are executed • Includes library of perceptual and motor schemas Tucker Balch Georgia Institute of Technology

24. Clay: Execution Hierarchy Hardware/Simulation Tucker Balch Georgia Institute of Technology

25. Building Blocks: Motor Schemas • Multiple independent processes each generate a vector combined by weighted summation • Computationally simple and fast • Enables design by composition. (Arkin 1989) • Related to artificial potential fields • Khatib (85), Krogh (84), Payton (89), Singh (98) Tucker Balch Georgia Institute of Technology

26. Motor Schemas: Move to Goal Tucker Balch Georgia Institute of Technology

27. Motor Schemas: Avoid Obstacle Tucker Balch Georgia Institute of Technology

28. Motor Schemas: Avoid Obstacle + Move to Goal Tucker Balch Georgia Institute of Technology

29. Example: Behaviors for Pushing Tucker Balch Georgia Institute of Technology

30. Specification at Initialization Time detect_home = new v_Goal_r(abstract_robot,0,0); move_to_home = new v_Attraction_v(detect_home); detect_obstacles = new va_Obstacles_r( abstract_robot); avoid_obstacles = new v_Avoid_va(2.0, 1.0, detect_obstacles); swirl_obstacles = new v_Swirl_va(2.0, 1.0, detect_obstacles, detect_goal); move_to_home swirl_obstacles avoid_obstacles detect_home detect_obstacles Tucker Balch Georgia Institute of Technology

31. Methods of Composition • Weighted sum • Winner take all • Perceptual sequencing • Learning Tucker Balch Georgia Institute of Technology

32. Example: Combining by Weighted Sum avoid_n_swirl = new StaticWeightedSum_va(); avoid_n_swirl.embedded[0] = avoid_obstacles; avoid_n_swirl.weights[0] = 0.5; avoid_n_swirl.embedded[1]= swirl_obstacles; avoid_n_swirl.weights[1] = 0.5; avoid_n_swirl.embedded[2] = move_to_home; avoid_n_swirl.weights[2] = 1.0; steering_configuration = avoid_n_swirl; avoid_n_swirl move_to_home swirl_obstacles avoid_obstacles detect_home detect_obstacles Tucker Balch Georgia Institute of Technology

33. Communication as Sensing detect_ball = new v_DetectRed_r(abstract_robot); team_ball_obs = va_CommRed_r(abstract_robot); ball_observations = v_Combine_vav(team_ball_obs, detect_ball); fused_ball_obs = v_Fuse_va(ball_observations); fused_ball_observaions ball_observations detect_ball team_ball_obs Tucker Balch Georgia Institute of Technology

34. Comments on Clay/Java • Nodes (schemas) are naturally embedded, combined and selected using Java syntax • Java provides type checking at configuration time • For node configuration • For robot/control system matching Tucker Balch Georgia Institute of Technology

35. Research & Education Using TeamBots • Robot formations (Balch & Hybinette) • Learning behaviors for soccer & foraging (Balch) • Cooperative observation and localization (Stroupe & Balch) • Learning behaviors for herding (Potter, des Jardins) • Pheromone-based behavior (Payton) • Robot soccer (Balch, Kitano) • Education: SoccerBots Tucker Balch Georgia Institute of Technology

36. Obtaining TeamBots • www.teambots.org • Free for non-commercial use • New release due June 1 Tucker Balch Georgia Institute of Technology

37. Summary • TeamBots architecture leverages OO/Java features to provide: • Rapid prototyping in simulation • Using well-defined API to robot hardware • Behavior specification using Clay (or not) • Easy to use robot-robot communication • Tested control systems run directly on robots Tucker Balch Georgia Institute of Technology