1. Towards Robot Theatre Marek Perkowski Department of Electrical and Computer Engineering, Portland State University, Portland, Oregon, 97207-0751

2. Humanoid Robots and Robot Toys

3. Talking Robots Many talking robots exist, but they are still very primitive Work with elderly and disabled Actors for robot theatre, agents for advertisement, education and entertainment. Designing inexpensive natural size humanoid caricature and realistic robot heads We concentrate on Machine Learning techniques used to teach robots behaviors, natural language dialogs and facial gestures. Dog.com from Japan Work in progress

4. Robot with a Personality? Future robots will interact closely with non-sophisticated users, children and elderly, so the question arises, how they should look like? If human face for a robot, then what kind of a face? Handsome or average, realistic or simplified, normal size or enlarged? Why is Kismet so successful? We believe that a robot that will interact with humans should have some kind of “personality” and Kismet so far is the only robot with “personality”. The famous example of a robot head is Kismet from MIT.

5. Robot face should be friendly and funny The Muppets of Jim Henson are hard to match examples of puppet artistry and animation perfection. We are interested in robot’s personality as expressed by its: –behavior, –facial gestures, –emotions, –learned speech patterns.

6. Behavior, Dialog and Learning Robot activity as a mapping of the sensed environment and internal states to behaviors and new internal states (emotions, energy levels, etc). Our goal is to uniformly integrate verbal and non-verbal robot behaviors. Words communicate only about 35 % of the information transmitted from a sender to a receiver in a human-to-human communication. The remaining information is included in para-language. Emotions, thoughts, decision and intentions of a speaker can be recognized earlier than they are verbalized. NASA

8. Morita’s Theory

9. Our Base Model and Designs

10. Neck and upper body movement generation

11. 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

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

13. 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.

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

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

16. 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

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

18. 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

19. Maria, 2002/2003 20 DOF

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

21. Animation of eyes and eyelids

22. Cynthia, 2004, June

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

24. 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.

25. 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.

26. Face features recognition and visualization.

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

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

29. Editing movements

30. Yangban the Aristocrat and Pune his concubine The Narrator

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

34. 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.

35. New Silicone Skins

36. 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.

37. Probabilistic and Finite State Machines

38. 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

39. 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

40. 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

41. 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”

42. Dialog and Robot’s Knowledge

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

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

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

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

47. 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

48. 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

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

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

51. Human-Asking Robot Human Question Human asks Question Robot asks

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

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

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

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

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

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

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

59. 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?

60. 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?

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

77. 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)

78. 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.

79. (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. (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

80. (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

81. Constructive Induction

83. Name (examples) Age (output) d SmileHeightHair Color Joan Kid (0) a(3)b(0)c(0) Mike Teenager (1) a(2)b(1)c(1) Peter Mid-age (2) a(1)b(2)c(2) Frank Old (3) a(0)b(3)c(3) Example “Age Recognition” Examples of data for learning, four people, given to the system

84. Smile - a Very often often moderately rarely Values 3210 Height - b Very Tall TallMiddleShort Values 3210 Color - c GreyBlackBrownBlonde Values 3210 Example “Age Recognition” Encoding of features, values of multiple-valued variables

85. Multi-valued Map for Data ab\ c0123 00---- 01---3 02---- 03---- 10---- 11---- 12--2- 13---- 20---- 21-1-- 22---- 23---- 300--- 31---- 32---- 33---- d = F( a, b, c ) ab\ c0123 00---- 01---3 02---- 03---- 10---- 11---- 12--2- 13---- 20---- 21-1-- 22---- 23---- 300--- 31---- 32---- 33---- Groups show a simple induction from the Data

86. Old people smile rarely ab\ c0123 00---- 01---3 02---- 03---- 10---- 11---- 12--2- 13---- 20---- 21-1-- 22---- 23---- 300--- 31---- 32---- 33---- Groups show a simple induction from the Data Middle-age people smile moderately Teenagers smile often Children smile very often Grey hair blonde hair

87. Another example: teaching movements Input variables Output variables

88. Generalization of the Ashenhurst- Curtis decomposition model

89. This kind of tables known from Rough Sets, Decision Trees, etc Data Mining

90. Decomposition is hierarchical At every step many decompositions exist Which decomposition is better? Original table First variant of decomposition Second variant

91. Constructive Induction: Technical Details U. Wong and M. Perkowski, A New Approach to Robot’s Imitation of Behaviors by Decomposition of Multiple-Valued Relations, Proc. 5 th Intern. Workshop on Boolean Problems, Freiberg, Germany, Sept. 19-20, 2002, pp. 265-270. A. Mishchenko, B. Steinbach and M. Perkowski, An Algorithm for Bi-Decomposition of Logic Functions, Proc. DAC 2001, June 18-22, Las Vegas, pp. 103-108. A. Mishchenko, B. Steinbach and M. Perkowski, Bi- Decomposition of Multi-Valued Relations, Proc. 10 th IWLS, pp. 35-40, Granlibakken, CA, June 12-15, 2001. IEEE Computer Society and ACM SIGDA.

92. Decision Trees, Ashenhurst/Curtis hierarchical decomposition and Bi-Decomposition algorithms are used in our software These methods create our subset of MVSIS system developed under Prof. Robert Brayton at University of California at Berkeley [2]. – The entire MVSIS system can be also used. The system generates robot’s behaviors (C program codes) from examples given by the users. This method is used for embedded system design, but we use it specifically for robot interaction. Constructive Induction

93. Ashenhurst Functional Decomposition Evaluates the data function and attempts to decompose into simpler functions. if A  B = , it is disjoint decomposition if A  B  , it is non-disjoint decomposition B - bound set A - free set F(X) = H( G(B), A ), X = A  B X

94. A Standard Map of function ‘z’ Bound Set Free Set a b \ c z Columns 0 and 1 and columns 0 and 2 are compatible column compatibility = 2 Explain the concept of generalized don’t cares

95. NEW Decomposition of Multi- Valued Relations if A  B = , it is disjoint decomposition if A  B  , it is non-disjoint decomposition F(X) = H( G(B), A ), X = A  B Relation A B X

96. Forming a CCG from a K-Map z Bound Set Free Set a b \ c Columns 0 and 1 and columns 0 and 2 are compatible column compatibility index = 2 C1C1 C2C2 C0C0 Column Compatibility Graph

97. Forming a CIG from a K-Map Columns 1 and 2 are incompatible chromatic number = 2 z a b \ c C1C1 C2C2 C0C0 Column Incompatibility Graph

98. A unified internal language is used to describe behaviors in which text generation and facial gestures are unified. This language is for learned behaviors. Expressions (programs) in this language are either created by humans or induced automatically from examples given by trainers. Constructive Induction

99. Braitenberg Vehicles and Quantum Automata Robots

100. Another Example: Braitenberg Vehicles and Quantum BV

101. Braitenberg Vehicles

102. Example 1: Simulation Quantum Circuits |0  |1  |x  |0  |1  |x  |0  |1  |x  VV†V† V = U |0  |1  V|x  |0  |1  |0  |1  |x  |0  |1  |0  |1  |x  ? Toffoli gate: Universal, uses controlled square root of NOT

103. Quantum Portland Faces

104. Conclusion. What did we learn (1) the more degrees of freedom the better the animation realism. Art and interesting behavior above certain threshold of complexity. (2) synchronization of spoken text and head (especially jaw) movements are important but difficult. Each robot is very different. (3) gestures and speech intonation of the head should be slightly exaggerated – superrealism, not realism.

105. Conclusion. What did we learn(cont) (4) Noise of servos: –the sound should be laud to cover noises coming from motors and gears and for a better theatrical effect. –noise of servos can be also reduced by appropriate animation and synchronization. (5) TTS should be enhanced with some new sound-generating system. What? (6) best available ATR and TTS packages should be applied. (7) OpenCV from Intel is excellent. (8) use puppet theatre experiences. We need artists. The weakness of technology can become the strength of the art in hands of an artist.

106. (9) because of a too slow learning, improved parameterized learning methods should be developed, but also based on constructive induction. (10) open question: funny versus beautiful. (11) either high quality voice recognition from headset or low quality in noisy room. YOU CANNOT HAVE BOTH WITH CURRENT ATR TOOLS. (12) low reliability of the latex skins and this entire technology is an issue. Conclusion. What did we learn(cont)

107. We won an award in PDXBOT 2004. We showed our robots to several audiences International Intel Science Talent Competition and PDXBOT 2004, 2005 Robot shows are exciting Our Goal is to build toys for 21-st Century and in this process, change the way how engineers are educated.

108. Commercial Value of Robot Toys and Theatres

109. Robot Toy Market - Robosapiens toy, poses in front of

110. Globalization Globalization implies that images, technologies and messages are everywhere, but at the same time disconnected from a particular social structure or context. (Alain Touraine) The need of a constantly expanding market for its products chases the bourgoise over the whole surface of the globe. It must nestle everywhere, settle everywhere, establish connections everywhere. (Marx & Engels, 1848)

111. India and China - what’s different? They started at the same level of wealth and exports in 1980 China today exports $ 184 Bn vs $ 34 Bn for India China’s export industry employs today over 50 million people (vs 2 m s/w in 2008, and 20 m in the entire organized sector in India today!) (> 60% of the world marketChina’s export industry consists of toys (> 60% of the world market), bicycles (10 m to the US alone last year), and textiles (a vision of having a share of > 50% of the world market by 2008)

112. Learning from Korea and Singapore The importance of Learning –To manufacture efficiently –To open the door to foreign technology and investment –To have sufficient pride in ones own ability to open the door and go out and build ones own proprietary identity To invest in fundamentals like Education to have the right cultural prerequisites for catching up To have pragmatism rule, not ideology

113. Samsung 1979 Started making microwaves 1980 First export order (foreign brand) 1983 OEM contracts with General Electric 1985 All GE microwaves made by Samsung 1987 All GE microwaves designed by Samsung 1990 The world’s largest microwave manufacturer - without its own brand 1990 Launch own brand outside Korea 2000 Samsung microwaves # 1 worldwide, twelve factories in twelve countries (including India, China and the US) 2003 – the largest electronics company in the world

114. How did Samsung do it? By learning from GE and other buyers By working very hard - 70 hour weeks, 10 days holiday By being very productive - 9 microwaves per person per day vs 4 at GE By meeting every delivery on time, even if it meant working 7-day weeks for six months By developing new models so well that it got GE to stop developing their own

115. Fundamental question for humanoid robot builders

116. Should we build humanoid robots? Man’s design versus robot’s design The humanoid robot is versatile and adaptive, it takes its form from a human, a design well-verified by Nature. Complete isomorphism of a humanoid robot with a human is very difficult to achieve (walking) and not even not entirely desired. All what we need is to adapt the robot maximally to the needs of humans – elderly, disabled, children, entertainment. Replicating human motor or sensor functionality are based on mechanistic methodologies, –but adaptations and upgrades are possible – for instance brain wave control or wheels Is it immoral?

117. Is it worthy to build humanoid robots? Can building a mechanistic digital synthetic version of man be anything less than a cheat when man is not mechanistic, digital nor synthetic? If reference for the “ultimate” robot is man, then there is little confusion about one’s aim to replace man with a machine.

118. Man & Machine Main reason to build machines in our likeness is to facilitate their integration in our social space: –SOCIAL ROBOTICS Robot should do many things that we do, like climbing stairs, but not necessarily in the way we do it – airplane and bird analogy. Humanoid robots/social robots should make our life easier.

119. The Social Robot “developing a brain”: –Cognitive abilities as developed from classical AI to modern cognitive ideas (neural networks, multi-agent systems, genetic algorithms…) “giving the brain a body”: –Physical embodiment, as indicated by Brooks [Bro86], Steels [Ste94], etc. “a world of bodies”: –Social embodiment A Social Robot is: –A physical entity embodied in a complex, dynamic, and social environment sufficiently empowered to behave in a manner conducive to its own goals and those of its community.

120. Anthropomorphism Social interaction involves an adaptation on both sides to rationalise each others actions, and the interpretation of the others actions based on one’s references Projective Intelligence: the observer ascribes a degree of “intelligence” to the system through their rationalisation of its actions

121. Anthropomorphism & The Social Robot Objectives –Augment human-robot sociality –Understand and rationalize robot behavior Embrace anthropomorphism BUT - How does the robot not become trapped by behavioral expectations? REQUIRED: A balance between anthropomorphic features and behaviors leading to the robot’s own identity

122. Finding the Balance Movement –Behavior (afraid of the light) –Facial Action Coding System Form –Physical construction –Degrees of freedom Interaction –Communication (robot-like vs. human voice) –Social cues/timing Autonomy Function & role –machine vs. human capabilities

123. Humanoid Robots Experiments and Research Tasks Autonomous mobile robots Emotion through motion “Projective emotion” Anthropomorphism Social behaviors Qualitative and quantitative analysis to a wide audience through online web-based experiments

124. The perception learning tasks Robot Vision:Robot Vision: 1.Where is a face? (Face detection) 2.Who is this person (Face recognition, learning with supervisor, person’s name is given in the process. 3.Age and gender of the person. 4.Hand gestures. 5.Emotions expressed as facial gestures (smile, eye movements, etc) 6.Objects hold by the person 7.Lips reading for speech recognition. 8.Body language.

125. The perception learning tasks Speech recognition:Speech recognition: 1.Who is this person (voice based speaker recognition, learning with supervisor, person’s name is given in the process.) 2.Isolated words recognition for word spotting. 3.Sentence recognition. Sensors.Sensors. 1.Temperature 2.Touch 3.movement

126. The behavior learning tasks Facial and upper body gestures:Facial and upper body gestures: 1.Face/neck gesticulation for interactive dialog. 2.Face/neck gesticulation for theatre plays. 3.Face/neck gesticulation for singing/dancing. Hand gestures and manipulation.Hand gestures and manipulation. 1.Hand gesticulation for interactive dialog. 2.Hand gesticulation for theatre plays. 3.Hand gesticulation for singing/dancing.

127. Learning the perception/behavior mappings 1.Tracking the human. 2.Full gesticulation as a response to human behavior in dialogs and dancing/singing. 3.Modification of semi-autonomous behaviors such as breathing, eye blinking, mechanical hand withdrawals, speech acts as response to person’s behaviors. 4.Playing games with humans. 5.Body contact with human such as safe gesticulation close to human and hand shaking.

128. What to emphasize in future work? We want to develop a general methodology for prototyping software/hardware systems for interactive robots that work in human environment. Image processing, voice recognition, speech synthesis, expressing emotions, recognizing human emotions. Machine Learning technologies. Safety, not hitting humans.

129. Can we build the first complete robot theatre in the world? Yes, if we will have more students who really want to learn practical skills and not only to take classes for grades. Robotics I, Robotics II, individual projects, RAS, high school students.

130. Where are we going? This is an adventure, we do not know where our research will lead us. This is truly interdisciplinary project. We need artists and psychologists. If this takes the social functions of a theatre, it is a theatre. Lessons from CAD and computer chess: knowledge and search rather than “super- intelligent logic mechanism”. Initial complexity of knowledge.

131. Lessons: –“degeneration” of robot soccer. –OMSI project and security –Laws about future robots, can he sue me? Our goal: build a working environment for: –Education –Entertainment –Verification of theories (bacteria foraging, social dynamics, Freud, immunological robots) –Verification of technologies (FPGA, clusters, net in chip technologies and AMBRIC). Many researchers will be able to base their own research on our environment. We provide the technical background for more advanced or artistic work. When there will be: – the first commercially successful robot theatre? –the first humanoid social robot?

132. Humanoid robots 1. Teachers and helpers: –Language teachers –Teaching children –Teaching disabled children –Helpers for disabled adults –Helpers for old people –Helpers and companions for mentally disabled

133. Humanoid robots 2. Toys: –Conversational toys for lonely girls and young woman –Human-like robots as pets. –Animal-like robots as pets. –Interactive theatres of little robots sold separately and collected to families.

134. Humanoid robots 3. Robot Theatres: –Battle Bots (already commercial) –Robot theatres for children, next generation of Chucky Cheese Pizza Theatres and Disney Worlds. –Avangarda theatres for Adults (Umatilla, sex, violence, special effects like head separation, interaction, battle bots of new generation, and large size robot theatres in the prerries). –Artistic robot theatres (none exist – see Japanese Bunraku and Noh single robots, Kissmet, aquarium and new robots of Cynthia Breazeal from MIT).

135. Humanoid robots 4. Kiosks and receptionists: –Toy-like and simplified (commercial products). –Realistic in view and size. –Mobile museum robots (commercial). –Wheeled humanoid robot of child-like size to be rented for exhibitions.

136. Humanoid robots 5. Top research robots: –Kissmet –Honda –Sony –Fujitsu –Hubo and KAIST –Samsung –Many Japanese 6. Commercial Robot kits. –Mobile robots –Walking robots –Heads –Humanoids small –Humanoids – childlike and expensive. Pino.

137. Existing technologies for robot theatre Mobile robots (battlebots, Los Angeles group, Carnegie Mellon Group) Walking animals Walking big humans with robotic featuresJapanese robots like trump playing Sony) Walking big humans with human-like features (head only - Albert Hubo, Small humans. Body on wheels. Head only Head with neck and shoulders. Upper body Head on wheels

138. New Robots 2005

139. "Nothing serious. Just stunts. There are dogs, dolls, faces that contort and are supposed to express emotion on a robot," he said. Mr Engelberger, an American, founded the world's first company making industrial robots in 1961 and became a specialist manufacturer of robots for hospitals. It was pointless, expensive and unnecessary for Japan, which today makes three-quarters of the world's robots, to tinker with trivial inventions like robotic house sitters that rang to say there was a burglary going on, he said. It made more sense to use the formidable amount of research that it had already done on personal robot technology to apply it to machines made for tasks that actually needed doing. Such as robots that could be told by elderly or infirm people to fetch a book from a shelf or find the television remote or get a beer from the fridge.

140. "I've talked to visiting nurses who say that older people have to go to the bathroom more often and are embarrassed to say to somebody in the house, 'Please take me to the bathroom again'. But who cares how many times you ask a robot to take you to the bathroom?" The future market for robots installed in the homes of elderly people was bigger than the luxury car market, he said, predicting that they would be leased out for $US500 ($673) per month. Human care-givers cost 10 times that, Mr Engelberger said, and nursing homes were higher still. "I know that there are things that a robot can't do. It's not going to bathe you and it's not going to dress you but it can be made to find the milk in the fridge," he said. What the $US8 billion robotics industry needs is for engineers to design practical robots for personal care. So why isn't more work being done? Mainly, Mr Engelberger thinks, it's because everyone is immersed in needless research and companies are distracted by the uneconomic quest for the humanoid, which he derides as toy making. "I say, stop it all … go for the whole damn schmeer … I've recently become an octogenarian and I'd ask you, please, hurry up."

141. Albert Hubo At an IT exhibition on the sidelines of the Asia-Pacific Economic Cooperation (APEC) summit in Busan, a participant shakes hands with a humanoid robot named “Albert Hubo” which has the face of Albert Einstein on Monday. The robot can walk and speak and expresses emotions by moving facial muscles

142. Albert Hubo meets President Bush Help me robo- Einstein, you’re my only hope

143. Fujitsu’s Enon is getting a job at the grocery store Enon will be helping Aeon customers with everything from packing shopping bags and picking up groceries to find their way around the store.

144. This is the new HAL- 5, or more specifically the Hybrid Assistive Limb. Bionic Suit. It’s developed as a walking aid for those who could use a bit of extra power, such as the disabled or apparently farmers who must add bags of sodium to their basement water softeners.

145. Walking Actors, Japan $1000 iXs Research Corp. robots at Tokyo’s International Robot Exhibition.

146. The Bandai BN-17 Swiffer bot Bandai BN-17 robot – anthropomorphized robot for cleaning.Bandai It can also handle your email and act as a security system

147. SORA, a receptionist robot The little bot sports a camera, microphone, and speaker for one way video conferencing with visitors, who can interface with an included touchscreen for information, and even scan a business card to show their identity to whoever is subjecting them to this robotic greeter.video conferencing Once they’re all approved, the robot can wave it’s arms at them and point out the directions to the office being displayed on the screen.

148. The WowWee Robosapien v2 The $230 second generation Robosapien v2 with remote from WowWee. The Robosapien v2 can see, hear, touch, and interact with you and his surroundings with a full range of fluid movement. Seething with attitude, his full- functioning arms with grippers allow him to pick-up and throw objects and then kung-fu your azz if you sass him. He features 100s of functions including a low-level gastro- intestinal condition resulting in the occasional air-biscuit or belch to your children’s (and yours, admit it) amusement. He’s also fully programmable which means you’ll find hacks-a- plenty in the open-source community allowing you to extend his functionality.

149. Questions to students 1.Learn about new robot toys and other toys that can be used in our theatre or converted to useful robots or their components. 2.Explain the concept of mapping architecture for a robot. Mapping being a combinational functions and mapping based on Finite State Machines. 3.Explain the concept of Probabilistic Finite State Machine and how it can be used to control movements of a robot. 4.How to use finite state machines and probabilistic machines for dialog and speech generation

150. Questions to students 5.Explain Morita Theory and think if it can be generalized. 6.Our robots have speech recognition and vision. Some have also sonar, infrared, touch and other sensors. What kind of sensors you would like to add and how you would like to program them for your applications. 7.What is your concept of interactive robot toy that would extend the ideas of our Theatre. 8.Write a script-scenario of conversation with robot that can be in 3 emotional states. The robot is a receptionist in Electrical Engineering Department at PSU.