1. CS 4630: Intelligent Robotics and Perception Case Study: Motor Schema-based Design Chapter 5 Tucker Balch

2. AMiRE October, 2001 Tucker Balch Georgia Institute of Technology What We’ve Covered History of Intelligent Robotics (Chapter 1) Hierarchical paradigm (Chapter 2) Biological basis for behavior-based control (Chapter 3) Overview of behavior based control (Chapter 4) Subsumption architecture (Chapter 4) Motor schema-based control (Chapter 4)

3. AMiRE October, 2001 Tucker Balch Georgia Institute of Technology Upcoming Today: case study of behavior-based control for multirobot team. Friday: TeamBots tutorial, new project assignment Monday: Midterm Exam Weds: Begin Chapter 5 (Sensing) Friday: Guest Lecture (Koenig)

4. AMiRE October, 2001 Tucker Balch Georgia Institute of Technology Social Potentials Balch & Arkin, IEEE Transactions on Robotics and Automation, 2000

5. AMiRE October, 2001 Tucker Balch Georgia Institute of Technology

6. AMiRE October, 2001 Tucker Balch Georgia Institute of Technology The Multi-Foraging Task

7. AMiRE October, 2001 Tucker Balch Georgia Institute of Technology Foraging Robots (1997) Balch, AI Magazine, 1997. Balch, Autonomous Robots, 2000.

8. AMiRE October, 2001 Tucker Balch Georgia Institute of Technology Foraging Robots (1997) Balch, AI Magazine, 1997. Balch, Autonomous Robots, 2000.

9. AMiRE October, 2001 Tucker Balch Georgia Institute of Technology Foraging Robots (1997) Balch, AI Magazine, 1997. Balch, Autonomous Robots, 2000.

10. AMiRE October, 2001 Tucker Balch Georgia Institute of Technology Foraging Robots (1997) Balch, AI Magazine, 1997. Balch, Autonomous Robots, 2000.

11. AMiRE October, 2001 Tucker Balch Georgia Institute of Technology Behavioral Sequencing SearchDeliver Red have red Aquire Red see red ~see red ~have red at red bin Acquire BlueDeliver Blue have blue see blue at blue bin ~see blue ~have blue

12. AMiRE October, 2001 Tucker Balch Georgia Institute of Technology Performance as Team Size Increases

13. AMiRE October, 2001 Tucker Balch Georgia Institute of Technology Problem: Inter-Robot Interference

14. AMiRE October, 2001 Tucker Balch Georgia Institute of Technology Heterogeneous Strategy 1: Specialization

15. AMiRE October, 2001 Tucker Balch Georgia Institute of Technology Heterogeneous Strategy 2: Territorial

16. AMiRE October, 2001 Tucker Balch Georgia Institute of Technology Performance Comparison

17. AMiRE October, 2001 Tucker Balch Georgia Institute of Technology Are Diversity and Performance Correlated? Need a measure of robot team diversity Approach: information theory

18. AMiRE October, 2001 Tucker Balch Georgia Institute of Technology Diversity and Performance Negatively Correlated in Foraging

19. AMiRE October, 2001 Tucker Balch Georgia Institute of Technology Diversity and Performance Positively Correlated in Soccer Homogeneous Team Heterogeneous Team

20. AMiRE October, 2001 Tucker Balch Georgia Institute of Technology

21. AMiRE October, 2001 Tucker Balch Georgia Institute of Technology Where We are Real-time Video Processing Behavioral Sequence Representation Learning Algorithms

22. AMiRE October, 2001 Tucker Balch Georgia Institute of Technology Observing and Modeling Live Multi- Agent Systems Motivation –Our agents should act intelligently in the presence of other agents: humans, external agents, adversaries Social insects: –Rich, multiagent interactions –Adversarial/territorial behaviors –Real biology in collaboration with entomologists

23. AMiRE October, 2001 Tucker Balch Georgia Institute of Technology Research Goal: Develop Algorithms That Enable Simultaneous tracking of all the individuals in a colony Recognition of individual and colony behaviors Learning of new single and multi-agent behavior models Application of the models to multi-agent software and robotic systems

24. AMiRE October, 2001 Tucker Balch Georgia Institute of Technology The complexity of ant society Holldobler & Wilson, 1990 Gordon, 1999

25. AMiRE October, 2001 Tucker Balch Georgia Institute of Technology Video of ant behaviors

26. AMiRE October, 2001 Tucker Balch Georgia Institute of Technology Finding Ants In Images (1) CMVision: Color-based tracking –Initially developed for tracking soccer robots –Classifies and segments regions according to color –100s of regions, 32 colors, 30Hz, low cost Bruce, Balch & Veloso, IROS-2000

27. AMiRE October, 2001 Tucker Balch Georgia Institute of Technology Finding ants in images (2) Approach: background subtraction Enables classification by color and motion B ij = (1 -  )B ij +  I ij Background Image Current Image Movement

28. AMiRE October, 2001 Tucker Balch Georgia Institute of Technology Associating observations with individuals The association problem –Best optimal algorithm O(n 3 ) –Greedy approach O(n 2 ) Noisy data presents additional challenges –Splitting, merging, drop-outs, pop-ups Current approach –“Greedy agents” leverage domain knowledge Future –Parallel implementations, Bayesian techniques (e.g. Xiang & Lesser), radar tracking techniques

29. AMiRE October, 2001 Tucker Balch Georgia Institute of Technology

30. AMiRE October, 2001 Tucker Balch Georgia Institute of Technology

31. AMiRE October, 2001 Tucker Balch Georgia Institute of Technology

32. AMiRE October, 2001 Tucker Balch Georgia Institute of Technology Analyzing the Spatial Behavior of a Colony

33. AMiRE October, 2001 Tucker Balch Georgia Institute of Technology No Food Available

34. AMiRE October, 2001 Tucker Balch Georgia Institute of Technology Food Available

35. AMiRE October, 2001 Tucker Balch Georgia Institute of Technology Vector Representation

36. AMiRE October, 2001 Tucker Balch Georgia Institute of Technology Recognition Task: Right Turn, Left Turn, Straight? Approach: Average turning angles over a window Classify turns according to average: –if A < - , right turn –if A > , left turn –otherwise, straight n is the window size

37. AMiRE October, 2001 Tucker Balch Georgia Institute of Technology Example

38. AMiRE October, 2001 Tucker Balch Georgia Institute of Technology Recognizing Behavior from Movement Traces Hypothesis: –Observed movement features considered over time can be used to classify the behavior of a physical agent Previous success in observation of soccer agents –Hidden Markov Models (Han & Veloso, 1999) Example features –binary: towards-food, at-food, towards-home, at- home –continuous: velocity, turn-rate, path randomness Example behaviors –foraging, patrolling, carrying, recruiting

39. AMiRE October, 2001 Tucker Balch Georgia Institute of Technology Hidden Markov Model Representation S1S3 S2 0.90.1 0.9 0.1 0.9 A B C AAABBBBBBBBBBBBCCABBBBBBBBBCCA

40. AMiRE October, 2001 Tucker Balch Georgia Institute of Technology Hidden Markov Model Representation S1S3 S2 0.90.1 0.9 0.1 0.9 A 0.8 B 0.1 C 0.1 A 0.1 B 0.8 C 0.1 A 0.1 B 0.1 C 0.8 ACABBBABBBCBBBBCAABBBBABBBBCCA

41. AMiRE October, 2001 Tucker Balch Georgia Institute of Technology Using HMMs for Recognition With the Viterbi Algorithm AAABBBBBBBBBBBBCCABBBBBBBBBCCA

42. AMiRE October, 2001 Tucker Balch Georgia Institute of Technology inspired by Han & Veloso, 1999

43. AMiRE October, 2001 Tucker Balch Georgia Institute of Technology

44. AMiRE October, 2001 Tucker Balch Georgia Institute of Technology

45. AMiRE October, 2001 Tucker Balch Georgia Institute of Technology

46. AMiRE October, 2001 Tucker Balch Georgia Institute of Technology

47. AMiRE October, 2001 Tucker Balch Georgia Institute of Technology

48. AMiRE October, 2001 Tucker Balch Georgia Institute of Technology Real-time Video Processing Behavioral Sequence Representation Recognition Algorithms Learning Algorithms

49. AMiRE October, 2001 Tucker Balch Georgia Institute of Technology Thanks to Zia Khan Manuela Veloso James Bruce Gak Kaminka Pat Riley Rande Shern Ashley Stroupe DARPA Control of Agent Based Systems (CoABS)

50. AMiRE October, 2001 Tucker Balch Georgia Institute of Technology http://www.cc.gatech.edu/~tucker

51. AMiRE October, 2001 Tucker Balch Georgia Institute of Technology www.cc.gatech.edu/~tucker www.cc.gatech.edu/~cprl

52. Observing Ants: Tracking and Analyzing the Behavior of Live Insects Tucker Balch Collaborative Perception and Robotics Lab

53. AMiRE October, 2001 Tucker Balch Georgia Institute of Technology