1. SLIDES SET NUMBER 1.

2. Class 478/578: General 1 1.My name is Marek Perkowski 2.You can call my Marek, or Dr. Perkowski or whatever you like. 3.This class is fun, at least for me. 4.I hope that you will have fun also. 5.We build practical robots – embedded systems 6.Class is graded based on practical achievements, a little bit similar to Capstone Project. 7.You can find all information on my webpage, find me through Google.

3. Class 478/578: General 2 1.If you are a graduate student your project is more difficult, otherwise the same. 2.Two homeworks and Project 3.No exam. 4.Student presentations (related to homeworks or projects) 5.I expect high quality of reports (many graduate students had publications based on these reports) 6.Robots connected to Internet (demo and explanation next Thursday).

4. Class 478/578: grading 1.Homework 1 – 10 % (evolutionary algorithms and foraging) 2.Homework 2 – 10 % (any subset of your project) 3.Presentation – 10 % 4.Project – 70 % 5.Groups – 1 to 5 students, group leader. 6.In final report, each student has a separate part to demonstrate his/her work. 7.Each student presents a separate presentation of his work.

5. Class 478/578: book 1.Braunl. –You can find slides to this book on internet –Book was ordered early but it must be reprinted “on demand”. –If you have no book, do not worry. All is in my slides. –Somebody told me that PDF of all text is also on internet Slides of my class on my webpage – look for “Embedded Robotics” on my main webpage. To find my webpage do search on Google “Marek Perkowski”

6. Class 478/578: your background 1.Programming –Matlab –C –C++ –Java 2.Some basic digital design and interfacing experience (only in some projects) 3.Some basic math, Boolean Algebra, probability. 4.Digital Signal Processing, Image Processing (for some projects, will be covered in debth in ECE 479 next quarter)

7. Class 478/578: your background review 1.Boolean functions, gates and circuits 2.Finite State Machines 3.Probabilistic State Machines 4.Grammars 5.Linked Lists 6.Arduino

8. Class 478/578: your background information Please give me today the following information: 1.Your first name, last name and contact (email, phone) 2.Do you want to be on my Facebook – send me message on Facebook. 3.Programming classes you have taken. 4.Programming projects you have done. 5.Robot projects you have done. Please write more. 6.Any hardware projects you have done, like fixing a radio or a computer, building a FPGA controller etc. 7.Your background (hardware, software, art, physics, math, biology, etc) 8.Are you a graduate or undergraduate student. 9.For each of three areas: theory, programming and practical robot building, write percentages of your project’s grade (I am not sure I will be able to take this into account in every case) 10.Do you prefer to work alone or in a team for this class?

9. Class 478/578: your background information Please give me today the following information: 1.Your first name, last name and contact (email, phone) 2.Do you want to be on my Facebook – send me message on Facebook. 3.Programming classes you have taken. 4.Programming projects you have done. 5.Robot projects you have done. Please write more. 6.Any hardware projects you have done, like fixing a radio or a computer, building a FPGA controller etc. 7.Your background (hardware, software, art, physics, math, biology, etc) 8.Are you a graduate or undergraduate student. 9.For each of three areas: theory, programming and practical robot building, write percentages of your project’s grade (I am not sure I will be able to take this into account in every case) 10.Do you prefer to work alone or in a team for this class?

10. Class 478/578: Projects and Lab 1.Meeting with Chris Clark 2.Meeting with class TA 3.Webpages with previous projects 4.Interfacing to internet 5.Lab keys (cards)

11. Class 478/578: Projects for this year 1.Dancing hexapods 2.Foraging hexapods 3.Robot Theatre 4.Sustainable Robot for advertising 5.Robot Guide for PSU 6.Robots controlled by iPhones, Ipads, etc. 7.Advanced theories for robotics (only for individual graduate students)

12. EMBEDDED SYSTEMS

13. Textbook: T. Bräunl Embedded Robotics, Springer 2003

14. Plan of class Week 1: –Servo programming –Evolutionary algorithms Week 2: –Humanoid Robots –Models of robotics Mapping, grammars, automata, probabilistic, Braitenberg Vehicles, natural language, logic based learning.

16. 1.1 Definition Definition for: embedded system A combination of hardware and software which together form a component of a larger machine. An example of an embedded system is a microprocessor that controls an automobile engine. An embedded system is designed to run on its own without human intervention, and may be required to respond to events in real time. Source: www.computeruser.com/resources/dictionary

17. Applications Areas

18. Application Areas TV stereo remote control phone / mobile phone refrigerator microwave washing machine electric tooth brush oven / rice or bread cooker watch alarm clock electronic musical instruments electronic toys (stuffed animals,handheld toys, pinballs, etc.) medical home equipment (e.g. blood pressure, thermometer) … [PDAs?? More like standard computer system] Consumer Products

19. Application Areas Medical Systems –pace maker, patient monitoring systems, injection systems, intensive care units, … Office Equipment –printer, copier, fax, … Tools –multimeter, oscilloscope, line tester, GPS, … Banking –ATMs, statement printers, … Transportation –(Planes/Trains/[Automobiles] and Boats) radar, traffic lights, signalling systems, …

20. Application Areas Automobiles –engine management, trip computer, cruise control, immobilizer, car alarm, –airbag, ABS, ESP, … Building Systems –elevator, heater, air conditioning, lighting, key card entries, locks, alarm systems, … Agriculture –feeding systems, milking systems, … Space –satellite systems, …

21. Application Areas Facts: –1997: The average U.S. household has over 10 embedded computers (source: www.it.dtu.dk/~jan)www.it.dtu.dk/~jan 1998: 90% Embedded Systems vs. 10% Computers –(source: Frautschi, www.caliberlearning.com) 2001: The Volvo S80 has 18 embedded controllers and 2 busses (source: Volvo)

22. Automobiles

25. Robot Metaphors and Models

26. Animatronic “Robot” or device brain effectors

27. Perceiving “Robot” brain sensors

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

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

30. Braitenberg Vehicles and Quantum Automata Robots

31. Another Example: Braitenberg Vehicles and Quantum BV

32. Braitenberg Vehicles

33. Braitenberg Vehicles: Homework 1 idea 1.Can you think about other robot behaviors? 2.Can you develop software for robots with other mechanics/kinematics but the same emergent principles? 3.Design circuits for switchable behaviors: like sound that switches from shy to aggressive robot.

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

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

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

37. Our First Base Robot Architecture and Designs

38. Neck and upper body movement generation

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

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

41. 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.

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

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

44. 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. BUG (Big Ugly Robot) 2002

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

46. Professor Perky 1 dollar latex skin from China 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. Professor Perky with automated speech recognition (ASR) and text-to-speech (TTS) capabilities 2002, Japan

47. Maria, 2002/2003 20 DOF

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

49. Animation of eyes and eyelids

50. Cynthia, 2004, June

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

52. 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.

53. 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.

54. Face features recognition and visualization.

55. Use of Multiple- Valued (five- valued) variables Smile, Mouth_Open and Eye_Brow_Raise for facial feature and face recognition.

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

57. Editing movements

58. Yangban the Aristocrat and Pune his concubine The Narrator

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

62. 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.

63. New Silicone Skins

64. 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.

65. Probabilistic and Finite State Machines

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

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

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

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

70. Dialog and Robot’s Knowledge

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

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

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

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

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

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

77. Human-Initiated Conversation Robot Human Hello Maria Robot asks initialization

78. Human-Initiated Conversation Robot Human Hello Maria What can I do for you? Robot asks

79. Human-Asking Robot Human Question Human asks Question Robot asks

80. Human-Asking Robot Human Question Human asks Yes, you ask a question.

81. Human-Asking Robot Human What book wrote Lee? Human asks Yes, you ask a question.

82. Human-Asking Robot Human What book wrote Lee? Human asks I have no sure information.

83. Human-Asking Robot Human Try to guess. Human asks I have no sure information.

84. Human-Asking Robot Human Try to guess. Human asks Lee wrote book “Flowers”.

85. Human-Asking Robot Human This is not true. Human asks Lee wrote book “Flowers”.

86. Human-Teaching Robot Human Questioning finished Human teaches “Questioning finished” Robot asks Human asks Thanks, I have a lesson Human ends questioning

87. Human-Teaching Robot Human Questioning finished Human teaches “Questioning finished” Robot asks Human asks Thanks, I have a lesson Robot enters asking mode What can I do for you?

88. Human-Teaching Robot Human Thanks, I have a lesson Human teaches “Questioning finished” Robot asks Human asks Thanks, I have a lesson Human starts teaching What can I do for you?

89. Human-Teaching Robot Human Thanks, I have a lesson Yes Human teaches

90. Human-Teaching Robot Human I give you question- answer pattern Yes Human teaches

91. Human-Teaching Robot Human Question pattern: What book Smith wrote? Yes Human teaches

92. Robot Human Answer pattern: Smith wrote book “Automata Theory” Yes Human teaches Human-Teaching

93. Human-Teaching Robot Human Checking question: What book wrote Smith? Yes Human teaches

94. Human-Teaching Robot Human Checking question: What book wrote Smith? Smith wrote book “Automata Theory” Human teaches

95. Human-Teaching Robot Human I give you question- answer pattern Yes Human teaches

96. Human-Teaching Robot Human Question pattern: Where is room of Lee? Yes Human teaches

97. Human-Teaching Robot Human Answer pattern: Lee is in room 332 Yes Human teaches

98. Human-Checking what robot learned Robot Human Lesson finished Human asks Question Robot asks Human teaches “Lesson finished”

99. Human-Checking what robot learned Robot Human Lesson finished Human asks Question Robot asks Human teaches “Lesson finished” What can I do for you?

100. Human-Checking what robot learned Robot Human Question Human asks Question Robot asks Human teaches “Lesson finished” What can I do for you?

101. Human-Asking Robot Human Question Human asks Question Robot asks Human teaches “Lesson finished” Yes, you ask a question.

102. Human-Asking Robot Human What book wrote Lee? Human asks Yes, you ask a question.

103. Human-Asking Robot Human What book wrote Lee? Human asks I have no sure information.

104. Human-Asking Robot Human Try to guess. Human asks I have no sure information.

105. Human-Asking Robot Human Try to guess. Human asks Lee wrote book “Automata Theory” Observe that robot found similarity between Smith and Lee and generalized (incorrectly)

106. Behavior, Dialog and Learning The dialog/behavior has the following components: –(1) Eliza-like natural language dialogs based on pattern matching and limited parsing. Commercial products like Memoni, Dog.Com, Heart, Alice, and Doctor all use this technology, very successfully – for instance Alice program won the 2001 Turing competition. –This is a “conversational” part of the robot brain, based on pattern-matching, parsing and black-board principles. –It is also a kind of “operating system” of the robot, which supervises other subroutines.

107. (2) Subroutines with logical data base and natural language parsing (CHAT). –This is the logical part of the brain used to find connections between places, timings and all kind of logical and relational reasonings, such as answering questions about Japanese geography. Behavior, Dialog and Learning

108. (3) Use of generalization and analogy in dialog on many levels. –Random and intentional linking of spoken language, sound effects and facial gestures. –Use of Constructive Induction approach to help generalization, analogy reasoning and probabilistic generations in verbal and non-verbal dialog, like learning when to smile or turn the head off the partner. Behavior, Dialog and Learning

109. (4) Model of the robot, model of the user, scenario of the situation, history of the dialog, all used in the conversation. (5) Use of word spotting in speech recognition rather than single word or continuous speech recognition. (6) Continuous speech recognition (Microsoft) (7) Avoidance of “I do not know”, “I do not understand” answers from the robot. –Our robot will have always something to say, in the worst case, over-generalized, with not valid analogies or even nonsensical and random. Behavior, Dialog and Learning

110. Questions to students 1.Present a concept of a robot with architecture based on combinational logic mapping. Design a function from gates. 2.Present a concept of a robot with architecture based on deterministic Finite State Machine. Show a graph or table of the machine. You can also draw a flowchart. 3.Present a concept of a robot with architecture based on probabilistic Finite State Machine. Show a graph or table of the machine. 4.Present a software internet robot for natural language conversation, similar to receptionist robot from this set of slides. The robot should discuss Intelligent Robotics Laboratory, its research, faculty and students. What are the “states of robot”? What are the key-words to transit from state to state, draw a diagram. 5.Analyze four different Braitenberg Vehicles based on a robot with kinematics of a standard car. Two of them can be similar to Shy and Aggressive robots from class. 6.Analyze four different “Braitenberg-like robots” that have a head and one hand. Two of them can be similar to Shy and Aggressive robots from class This is not a homework, just to test your knowledge. You do not have to give it to me but you may if you want.