Robot Metaphors and Models

1. Robot Metaphors and Models

2. Animatronic “Robot” or device brain effectors

3. Perceiving “Robot” brain sensors

4. Reactive Robot is the simplest behavioral robot Brain is a mapping sensors effectors This is the simplest robot that satisfies the definition of a robot

5. Reactive Robot in environment ENVIRONMENT is a feedback brain sensors effectors This is the simplest robot that satisfies the definition of a robot

6. Braitenberg Vehicles and Quantum Automata Robots

7. Another Example: Braitenberg Vehicles and Quantum BV

8. Braitenberg Vehicles

9. Emotional Robot has a simple form of memory or state Brain is a Finite State Machine sensors effectors This is the simplest robot that satisfies the definition of a robot

10. Behavior as an interpretation of a string • Newton, Einstein and Bohr. • Hello Professor • Hello Sir • Turn Left . Turn right. behavior

11. Behavior as an interpretation of a tree • Newton, Einstein and Bohr. • Hello Professor • Hello Sir • Turn Left . Turn right. behavior Grammar. Derivation. Alphabets.

12. Our Base Model and Designs

13. Neck and upper body movement generation

14. Robot Head Construction, 1999 High school summer camps, hobby roboticists, undergraduates Furby head with new control Jonas We built and animated various kinds of humanoid heads with from 4 to 20 DOF, looking for comical and entertaining values.

15. Mister Butcher Latex skin from Hollywood 4 degree of freedom neck

16. Robot Head Construction, 2000 Skeleton Alien We use inexpensive servos from Hitec and Futaba, plastic, playwood and aluminum. The robots are either PC-interfaced, use simple micro-controllers such as Basic Stamp, or are radio controlled from a PC or by the user.

17. Technical Construction, 2001 Details Marvin the Crazy Robot Adam

18. 2001 Virginia Woolf heads equipped with microphones, USB cameras, sonars and CDS light sensors

19. 2002 BUG (Big Ugly Robot) Max Image processing and pattern recognition uses software developed at PSU, CMU and Intel (public domain software available on WWW). Software is in Visual C++, Visual Basic, Lisp and Prolog.

20. Visual Feedback and Learning based on Constructive Induction 2002 Uland Wong, 17 years old

21. 2002, Japan Professor Perky Professor Perky with automated speech recognition (ASR) and text-to-speech (TTS) capabilities • We compared several commercial speech systems from Microsoft, Sensory and Fonix. • Based on experiences in highly noisy environments and with a variety of speakers, we selected Fonix for both ASR and TTS for Professor Perky and Maria robots. • We use microphone array from Andrea Electronics. 1 dollar latex skin from China

22. Maria, 2002/2003 20 DOF

23. location of head servos Construction details of Maria skull • location of controlling rods • location of remote servos Custom designed skin

24. Animation of eyes and eyelids

25. Cynthia, 2004, June

26. Currently the hands are not moveable. We have a separate hand design project.

27. Software/Hardware Architecture • Network- 10 processors, ultimately 100 processors. • Robotics Processors. ACS 16 • Speech cards on Intel grant • More cameras • Tracking in all robots. • Robotic languages – Alice and Cyc-like technologies.

28. Face detection localizes the person and is the first step for feature and face recognition. Acquiring information about the human: face detection and recognition, speech recognition and sensors.

29. Face features recognition and visualization.

30. Use of Multiple-Valued (five-valued) variablesSmile, Mouth_Open and Eye_Brow_Raise for facial feature and face recognition.

31. HAHOE KAIST ROBOT THEATRE, KOREA, SUMMER 2004 Czy znacie dobra sztuke dla teatru robotow? Sonbi, the Confucian Scholar Paekchong, the bad butcher

32. Editing movements

33. Yangban the Aristocrat and Pune his concubine The Narrator

34. The Narrator

36. We base all our robots on inexpensive radio-controlled servo technology.

37. We are familiar with latex and polyester technologies for faces Martin Lukac and Jeff Allen wait for your help, whether you want to program, design behaviors, add muscles, improve vision, etc.

38. New Silicone Skins

39. A simplified diagram of software explaining the principle of using machine learning based on constructive induction to create new interaction modes of a human and a robot.

40. Probabilistic and Finite State Machines

41. Probabilistic State Machines to describe emotions “you are beautiful” / ”Thanks for a compliment” P=1 Happy state “you are blonde!” / ”I am not an idiot” P=0.3 “you are blonde!” / Do you suggest I am an idiot?” Unhappy state P=0.7 Ironic state

42. Facial Behaviors of Maria Do I look like younger than twenty three? Maria asks: Response: • “no” • “no” • “yes” 0.7 0.3 Maria smiles Maria frowns

43. Probabilistic Grammars for performances Speak ”Professor Perky”, blinks eyes twice P=0.1 Speak ”Professor Perky” Where? P=0.3 Who? P=0.5 P=0.5 P=0.5 Speak “in some location”, smiles broadly Speak “In the classroom”, shakes head Speak ”Doctor Lee” What? P=0.1 P=0.1 P=0.1 Speak “Was singing and dancing” P=0.1 Speak “Was drinking wine” ….

44. Human-controlled modes of dialog/interaction Human teaches “Thanks, I have a lesson” “Hello Maria” “Lesson finished” Robot performs Robot asks “Question” “Stop performance” “Questioning finished” “Command finished” “Thanks, I have a question” “Thanks, I have a command” Human asks Human commands

45. Dialog and Robot’s Knowledge

46. Robot-Receptionist Initiated Conversation Human Robot What can I do for you? Robot asks This represents operation mode

47. Robot-Receptionist Initiated Conversation Human Robot What can I do for you? I would like to order a table for two Robot asks

48. Robot-Receptionist Initiated Conversation Human Robot Smoking or non-smoking? Robot asks

49. Robot-Receptionist Initiated Conversation Human Robot Smoking or non-smoking? I do not understand Robot asks

50. Robot-Receptionist Initiated Conversation Human Robot Do you want a table in a smoking or non-smoking section of the restaurant? Non-smoking section is near the terrace. Robot asks