1. The TeamBots Environment
Tucker Balch
The Borg Lab
Georgia Institute of Technology
Wonderful to be here!
This is work led by me in collaboration with my graduate students at CMU
I am going to focus on work begun over the last year that I plan to continue in the future
General -- collaborations

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
Mobile Robot Programming
10 May 2002

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
Mobile Robot Programming
10 May 2002

4. TeamBots Software Architecture: Design
Robot Controller
API
Simulation
Hardware
Tucker Balch
Georgia Institute of Technology
Mobile Robot Programming
10 May 2002

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
Mobile Robot Programming
10 May 2002

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
Mobile Robot Programming
10 May 2002

7. Example TeamBots Simulations
RoboCup small size soccer
Nomad 150
Probotics Cye vehicle
Outdoor vehicles
Robot Controller
API
Simulation
Tucker Balch
Georgia Institute of Technology
Mobile Robot Programming
10 May 2002

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
Mobile Robot Programming
10 May 2002

9. TBSim Implementation Control Systems Simulated World
Robot 1 Control System
Robot 2 Control System
simulated obstacle
Simulated World
simulated obstacle
simulated robot hardware
simulated obstacle
simulated robot hardware
simulated obstacle
Tucker Balch
Georgia Institute of Technology
Mobile Robot Programming
10 May 2002

10. Description File Syntax
bounds –5 5 5 –5 // meters
timestep // milliseconds
timeout // milliseconds
trials 10
graphics on
seed 993
windowsize // pixels
object Obstacle x0000FF x
robot Nomad150 forage x xFF0000 2
Tucker Balch
Georgia Institute of Technology
Mobile Robot Programming
10 May 2002

11. 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)
Robot Controller
API
Hardware
Tucker Balch
Georgia Institute of Technology
Mobile Robot Programming
10 May 2002

12. TBHard java TBHard Nomad150 forage desoto.cc.gatech.edu 3 600 0 0 0
Tucker Balch
Georgia Institute of Technology
Mobile Robot Programming
10 May 2002

13. Nomad 150 Balch, AI Magazine, 1997. Balch, Autonomous Robots, 2000.
Tucker Balch
Georgia Institute of Technology
Mobile Robot Programming
10 May 2002

14. Nomad 150 Balch, AI Magazine, 1997. Balch, Autonomous Robots, 2000.
Tucker Balch
Georgia Institute of Technology
Mobile Robot Programming
10 May 2002

15. Nomad 150 Balch, AI Magazine, 1997. Balch, Autonomous Robots, 2000.
Tucker Balch
Georgia Institute of Technology
Mobile Robot Programming
10 May 2002

16. Nomad 150 Balch, AI Magazine, 1997. Balch, Autonomous Robots, 2000.
Tucker Balch
Georgia Institute of Technology
Mobile Robot Programming
10 May 2002

17. Probotics’ Cye Tucker Balch Georgia Institute of Technology
Mobile Robot Programming
10 May 2002

18. How Robot APIs are Defined
Make use of Java features
Inheritance
Interfaces
Robot Controller
API
Simulation
Hardware
Tucker Balch
Georgia Institute of Technology
Mobile Robot Programming
10 May 2002

19. Robot API Hierarchy: Design
Simple
extends
Nomad150
Nomad150Hard
Nomad150Sim
implements
extends
Nomad150Comm
Nomad150CommSim
Nomad150CommHard
implements
Tucker Balch
Georgia Institute of Technology
Mobile Robot Programming
10 May 2002

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
Mobile Robot Programming
10 May 2002

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
Mobile Robot Programming
10 May 2002

22. Inter-Robot Communication
t.unicast(2, new stringMessage( "hello!"));
if (r.hasMoreElements())
new_message = r.getNextElement();
Tucker Balch
Georgia Institute of Technology
Mobile Robot Programming
10 May 2002

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
Mobile Robot Programming
10 May 2002

24. Clay: Execution Hierarchy
Hardware/Simulation
Tucker Balch
Georgia Institute of Technology
Mobile Robot Programming
10 May 2002

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
Mobile Robot Programming
10 May 2002

26. Motor Schemas: Move to Goal
Tucker Balch
Georgia Institute of Technology
Mobile Robot Programming
10 May 2002

27. Motor Schemas: Avoid Obstacle
Tucker Balch
Georgia Institute of Technology
Mobile Robot Programming
10 May 2002

28. Motor Schemas: Avoid Obstacle + Move to Goal
Tucker Balch
Georgia Institute of Technology
Mobile Robot Programming
10 May 2002

29. Example: Behaviors for Pushing
Tucker Balch
Georgia Institute of Technology
Mobile Robot Programming
10 May 2002

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
Mobile Robot Programming
10 May 2002

31. Methods of Composition
Weighted sum
Winner take all
Perceptual sequencing
Learning
Tucker Balch
Georgia Institute of Technology
Mobile Robot Programming
10 May 2002

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
Mobile Robot Programming
10 May 2002

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
Mobile Robot Programming
10 May 2002

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
Mobile Robot Programming
10 May 2002

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
Mobile Robot Programming
10 May 2002

36. Obtaining TeamBots www.teambots.org Free for non-commercial use
New release due June 1
Tucker Balch
Georgia Institute of Technology
Mobile Robot Programming
10 May 2002

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
Mobile Robot Programming
10 May 2002