Robot Towards Theatre
Marek Perkowski
Department of Electrical and Computer Engineering, Portland State University, Portland, Oregon, 97207-0751
Humanoid Robots and Robot Toys
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 Dog.com from Japan entertainment. Designing inexpensive We concentrate on Machine Learning natural size humanoid techniques used to teach robots caricature and realistic behaviors, natural language dialogs robot heads
and facial gestures. Work in progress
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?
The famous example of a robot head is Kismet from MIT.
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.
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 robots personality as expressed by its:
behavior, facial gestures, emotions, learned speech patterns.
Behavior, Dialog and Learning
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
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.
Moritas Theory
Our Base Model and Designs
Fig. 1. Learning Behaviors as Mappings from environments features to interaction procedures probability Speech from microphones Image features from cameras Sonars and other sensors Automatic software construction
from examples
(decision tree, bibidecomposition, Ashenhurst, Ashenhurst, DNF)
Verbal response generation (text response and TTS). Stored sounds Head movements and facial emotions generation Neck Neckshoulders and and upper movement movement body generation
generation
Emotions and knowledge memory
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.
Mister Butcher
Latex skin from Hollywood
4 degree of freedom neck
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.
Technical Construction, 2001 Details
Adam
Marvin the Crazy Robot
Virginia Woolf 2001
heads equipped with microphones, USB cameras, sonars and CDS light sensors
2002
Max
BUG (Big Ugly Robot)
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.
Visual Feedback and Learning based on Constructive Induction
Uland Wong, 17 years old
2002
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.
1 dollar latex skin from China
We use microphone array from Andrea Electronics.
Maria, 2002/2003
20 DOF
Construction details of Maria
skull
location of head servos
location of controlling rods
Custom designed skin
location of remote servos
Animation of eyes and eyelids
Cynthia, 2004, June
Currently the hands are not moveable. We have a separate hand design project.
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.
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.
Face features recognition and visualization.
Use of MultipleValued (fivevalued) variables Smile, Mouth_Open and Eye_Brow_Raise for facial feature and face recognition.
HAHOE KAIST ROBOT THEATRE, KOREA, SUMMER 2004
Czy znacie dobra sztuke dla teatru robotow? Sonbi, the Confucian Scholar Paekchong, the bad butcher
Editing movements
Yangban the Aristocrat and Pune his concubine
The Narrator
The Narrator
We base all our robots on inexpensive radiocontrolled servo technology.
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.
New Silicone Skins
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.
Probabilistic and Finite State Machines
Probabilistic State Machines to describe emotions
you are beautiful
P=1
/ Thanks for a compliment you are blonde!
P=0.3
Happy state
you are blonde! / Do you suggest I am an idiot? P=0.7
/ I am not an idiot
Unhappy state
Ironic state
Facial Behaviors of Maria
Maria asks: Response: yes
0.3
Do I look like younger than twenty three?
no
no
0.7
Maria smiles
Maria frowns
Probabilistic Grammars for performances
Speak Professor Perky, blinks eyes twice
P=0.1
Speak Professor Perky
P=0.3
Where?
P=0.5 P=0.5
Speak In the classroom, shakes head Speak in some location, smiles broadly
Who?
P=0.5
Speak Doctor Lee
P=0.1
What?
Speak Was singing and dancing
P=0.1 P=0.1 P=0.1
Speak Was drinking wine
.
Human-controlled modes of dialog/interaction
Hello Maria Thanks, I have a lesson
Human teaches
Lesson finished Question
Robot performs Stop performance Thanks, I have a question
Robot asks
Questioning finished Thanks, I have a command
Command finished
Human asks
Human commands
Dialog and Robots Knowledge
Robot-Receptionist Initiated Conversation
Robot Human
What can I do for you?
Robot asks This represents operation mode
Robot-Receptionist Initiated Conversation
Robot Human
What can I do for you?
I would like to order a table for two
Robot asks
Robot-Receptionist Initiated Conversation
Robot Human
Smoking or nonsmoking?
Robot asks
Robot-Receptionist Initiated Conversation
Robot Human
Smoking or nonsmoking?
I do not understand
Robot asks
Robot-Receptionist Initiated Conversation
Robot Human
Do you want a table in a smoking or non-smoking section of the restaurant? Non-smoking section is near the terrace.
Robot asks
Robot-Receptionist Initiated Conversation
Robot Human
Do you want a table in a smoking or non-smoking section of the restaurant? Non-smoking section is near the terrace.
A table near the terrace, please
Robot asks
Human-Initiated Conversation
Robot
Human
Hello Maria initialization Robot asks
Human-Initiated Conversation
Robot
Human
What can I do for you?
Hello Maria
Robot asks
Human-Asking
Robot
Human
Question
Robot asks
Question
Human asks
Human-Asking
Robot
Human
Yes, you ask a question.
Question
Human asks
Human-Asking
Robot
Human
Yes, you ask a question.
What book wrote Lee?
Human asks
Human-Asking
Robot
Human
I have no sure information.
What book wrote Lee?
Human asks
Human-Asking
Robot
Human
I have no sure information.
Try to guess.
Human asks
Human-Asking
Robot
Human
Lee wrote book Flowers.
Try to guess.
Human asks
Human-Asking
Robot
Human
Lee wrote book Flowers.
This is not true.
Human asks
Human-Teaching
Human ends questioning
Robot
Human
Questioning finished
Human asks
Questioning finished
Human teaches
Robot asks
Thanks, I have a lesson
Human-Teaching
Robot enters asking mode
Robot
Human
What can I do for you?
Questioning finished
Human asks
Questioning finished
Human teaches
Robot asks
Thanks, I have a lesson
Human-Teaching
Human starts teaching
Robot
Human
What can I do for you?
Thanks, I have a lesson
Human asks
Questioning finished
Human teaches
Robot asks
Thanks, I have a lesson
Human-Teaching
Robot
Human
Yes
Thanks, I have a lesson
Human teaches
Human-Teaching
Robot
Human
Yes
I give you questionanswer pattern
Human teaches
Human-Teaching
Robot
Human
Question pattern: Yes What book Smith wrote?
Human teaches
Human-Teaching
Robot
Human
Answer pattern: Yes Smith wrote book Automata Theory
Human teaches
Human-Teaching
Robot
Human
Checking question: Yes What book wrote Smith?
Human teaches
Human-Teaching
Robot
Human
Checking question: Smith wrote book Automata Theory What book wrote Smith?
Human teaches
Human-Teaching
Robot
Human
Yes
I give you questionanswer pattern
Human teaches
Human-Teaching
Robot
Human
Question pattern: Yes Where is room of Lee?
Human teaches
Human-Teaching
Robot
Human
Answer pattern: Yes Lee is in room 332
Human teaches
Human-Checking what robot learned
Robot Human
Lesson finished Human teaches
Robot asks
Lesson finished Question
Human asks
Human-Checking what robot learned
Robot Human
What can I do for you? Lesson finished Question
Lesson finished Human teaches
Robot asks
Human asks
Human-Checking what robot learned
Robot Human
What can I do for you? Lesson finished Question
Question Human teaches
Robot asks
Human asks
Human-Asking
Robot
Human
Yes, you ask a question. Lesson finished Question
Question Human teaches
Robot asks
Human asks
Human-Asking
Robot
Human
Yes, you ask a question.
What book wrote Lee?
Human asks
Human-Asking
Robot
Human
I have no sure information.
What book wrote Lee?
Human asks
Human-Asking
Robot
Human
I have no sure information.
Try to guess.
Human asks
Human-Asking
Robot
Human
Lee wrote book Automata Theory
Try to guess.
Observe that robot found similarity between Smith and Lee and generalized (incorrectly)
Human asks
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.
Behavior, Dialog and Learning
(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
(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.
Constructive Induction
Fig. 3. Question Answering by induction of answer parameters.
Input Variab les A: 0=what, 1= whe re, B: 0=wrote, 1= is, C: 0=book , 1=room, D: 0= Smith, 1=Lee Out put Variables X: 0=Smith, 1= Lee, 2=Perkowski, Y: 0= wr ote , 1=is, Z: 0= book, 1=room, 2=building, V: 0=332, 1=73, 2= 245, 3= Au tomata Theory, 4=Logic De sign
0000=what wrote book Smith? 0111=what is room Lee? 1111=where is room Lee?
New Question:
AB
CD 00
01 11
10
00
01 11 10
0,0,0,3
-
-
-
-
-
-
0001: What wrote book Lee? Example Answer = Smith wrote book Automata Theory Example Answer = Lee is room 332
1,1,1,0
- -
-
X,Y,Z,V
Example Age Recognition
Name (examples) Joan Mike Peter Frank
Age (output) d
Smile a(3) a(2) a(1) a(0)
Height b(0) b(1) b(2) b(3)
Hair Color c(0) c(1) c(2) c(3)
Kid (0)
Teenager
(1)
Mid-age
(2) Old (3)
Examples of data for learning, four people, given to the system
Example Age Recognition
Smile - a Values Height - b Values Color - c Values Very often often 3 Very Tall 2 Tall
moderately
rarely 0 Short 0 Blonde 0
1 Middle
3 2 1 Grey Black Brown 3 2 1
Encoding of features, values of multiple-valued variables
Multi-valued Map for Data
ab\ c 00 01 02 03 10 11 12 13 20 21 22 23 30 31 32 33 0 0 1 1 2 2 3 3 ab\ c 00 01 02 03 10 11 12 13 20 21 22 23 30 31 32 33
Groups show a simple induction from the Data
0 0 1 1 2 2 3 3 -
d = F( a, b, c )
Groups show a simple induction from the Data
blonde hair
Grey hair
0 0 1 1 2 2 3 3 -
ab\ c 00
Old people smile rarely
01 02 03 10
Middle-age people smile moderately
11 12 13 20 21 22 23 30 31 32 33
Teenagers smile often
Children smile very often
Another example: teaching movements
Fig. 2. Seven examples (4-input, 2 output minterms) are given by the teacher as correct robot behaviors Robot turns head right, away from light in left
CD AB
Robot turns head left, away from light in right, towards sound in left
Robot turns head left with equal front lighting and no sound. It blinks eyes
Ar ight micr ophone Bleftlightse nsor
Input variables
00 01 11 10
00 01 11 10
1,0 2,0 0,0 1,0 1,1
-
Crightlightsensor Dleftm icr ophone
- 0,0 - 0,0 - -
Robot does nothing Head_Horiz , Eye_Blink
Output variables
Generalization of the AshenhurstCurtis decomposition model
This kind of tables known from Rough Sets, Decision Trees, etc Data Mining
Original table First variant of decomposition Second variant
Decomposition is hierarchical
At every step many decompositions exist
Which decomposition is better?
Constructive Induction: Technical Details
U. Wong and M. Perkowski, A New Approach to Robots Imitation of Behaviors by Decomposition of Multiple-Valued Relations, Proc. 5th 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, BiDecomposition of Multi-Valued Relations, Proc. 10th IWLS, pp. 35-40, Granlibakken, CA, June 12-15, 2001. IEEE Computer Society and ACM SIGDA.
Constructive Induction
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 robots 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.
Ashenhurst Functional Decomposition
Evaluates the data function and attempts to decompose into simpler functions.
F(X) = H( G(B), A ), X = A B X
B - bound set
A - free set
if A B = , it is disjoint decomposition if A B , it is non-disjoint decomposition
A Standard Map of function z
ab\c
Bound Set
Explain the concept of generalized dont cares
Columns 0 and 1 and columns 0 and 2 are compatible
Free Set
column compatibility = 2
z
NEW Decomposition of Multi-Valued Relations
F(X) = H( G(B), A ), X = A B
Relation
Relation
X
A
B
if A B = , it is disjoint decomposition if A B , it is non-disjoint decomposition
Relation
Forming a CCG from a K-Map
ab\c
Bound Set
Columns 0 and 1 and columns 0 and 2 are compatible column compatibility index = 2
C0
Free Set
C1
C2
z
Column Compatibility Graph
ab\c
Forming a CIG from a K-Map
Columns 1 and 2 are incompatible chromatic number = 2
C0
C1
z
C2
Column Incompatibility Graph
Constructive Induction
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.
Braitenberg Vehicles and Quantum Automata Robots
Another Example: Braitenberg Vehicles and Quantum BV
Braitenberg Circuits
Toffoli Vehicles
Quantum gate: Universal, uses controlled square root of NOT
| 0 | 1 |
|0 |1
|
|0 |1
| 0 | 1
|0 |1
| 0 | 1
| 0 |
=
?
0 | 1 |
U
|x
V
V|x
V
|x
V
1 | x
Example 1: Simulation
x x
Quantum Portland Faces
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.
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.
Conclusion. What did we learn(cont)
(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.
Robot shows are exciting
We won an award in PDXBOT 2004. We showed our robots to several audiences
International Intel Science Talent Competition and PDXBOT 2004, 2005
Our Goal is to build toys for 21-st Century and in this process, change the way how engineers are educated.
Commercial Value of Robot Toys and Theatres
Robot Toy Market - Robosapiens
toy, poses in front of
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)
India and China - whats different?
They started at the same level of wealth and exports in 1980 China today exports $ 184 Bn vs $ 34 Bn for India Chinas 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!) Chinas export industry consists of toys (> 60% of the world market), bicycles (10 m to the US alone last year), market and textiles (a vision of having a share of > 50% of the world market by 2008)
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
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 worlds largest microwave manufacturer without its own brand 1990 Launch own brand outside Korea 1 Samsung microwaves # 1 worldwide, twelve factories in twelve countries (including India, China and the US)
2003 the largest electronics company in the world
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
Fundamental question for humanoid robot builders
Mans design versus robots 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
Should we build humanoid robots?
Is it immoral?
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 ones aim to replace man with a machine.
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.
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.
Anthropomorphism
Social interaction involves an adaptation on both sides to rationalise each others actions, and the interpretation of the others actions based on ones references Projective Intelligence: the observer ascribes a degree of intelligence to the system through their rationalisation of its actions
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 robots own identity
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
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
The perception learning tasks
Robot Vision:
1. Where is a face? (Face detection) 2. Who is this person (Face recognition, learning with supervisor, persons 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.
The perception learning tasks
Speech recognition:
1. Who is this person (voice based speaker recognition, learning with supervisor, persons name is given in the process.) 2. Isolated words recognition for word spotting. 3. Sentence recognition.
Sensors.
1. Temperature 2. Touch 3. movement
The behavior learning tasks
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.
1. Hand gesticulation for interactive dialog. 2. Hand gesticulation for theatre plays. 3. Hand gesticulation for singing/dancing.
Learning the perception/behavior mappings
1. Tracking the human. 1. Full gesticulation as a response to human behavior in dialogs and dancing/singing. 2. Modification of semi-autonomous behaviors such as breathing, eye blinking, mechanical hand withdrawals, speech acts as response to persons behaviors. 3. Playing games with humans. 4. Body contact with human such as safe gesticulation close to human and hand shaking.
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.
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.
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 superintelligent logic mechanism. Initial complexity of knowledge.
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?
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
H...