Theme 3: Most Advanced
Technologies of Robots:
An investigation of the most advance technologies for robots, both usefulness and novelties…

How has Robots been improved and how it will revolutionize the World?

Who We are………………………...........
•

Presented by:– Glenn Lee• Robotics Lead Teacher (1999-present) and Coordinator (2003-present)-CTE Industrial
Engineering Technology Career Pathway• STEM Learning Center Coordinator, Career Technical Education Coordinator, former
Extended Learning Opportunity (ELO) Project Director, School Technology Cadre andLeadership Team, Fine Arts/PE/AV/CTE dept. head.
• Degree in Electrical Engineering, minor in Math, M.B.A., Teaching Certificate inSecondary Education (Mathematics, Science, and Industrial Engineering & Technology)–

Pressented by: Waialua Robotics Program
Student Participants-Research Project: Kobe Lunasco, Cody Miyataki, Megan
Andrada, Draven Ozoa, Isabelle Pescaia, Toshio Yoshizumi
Waialua High & Intermediate School (Waialua, HI)
Group #12

Technology Readiness Level….

Waialua, Hawaii and the Waialua Robotics Program• Established in August 1999 as part of a STEM initiative to encourage students to major
in Science, Technology, Engineering and Mathematics. In 1999, only 1 student from thegraduating class applied for an engineering program.
• Waialua, Hawaii is a rural community Many of the current families living in Waialua are
the results of agricultural industry which began in the early 1900s. During the late 1980s
and into the 1990s, the sugar production decreased as increasing labor and production
costs caused producers to move overseas. Many of the families brought to Waialua
during the sugar rush remained here and many of their descendants reside there today.

Most Advanced Technologies of
Robots.............Artificial Intelligence (AI)Artificial Intelligence (Autonomous)Technology Readiness Levels (TRL) area method of estimating technology maturityof Critical Technology Elements (CTE) of aprogram during the acquisition process.
They are determined during a Technology
Readiness Assessment (TRA) thatexamines program concepts, technology
requirements, and demonstrated
technology capabilities. TRL are based ona scale from 1 to 9 with 9 being the mostmature technology. The use of TRLs
enables consistent, uniform, discussions oftechnical maturity across different types oftechnology•
What is Artificial Intelligence (AI)?
-It is the science and engineering of making intelligent machines, especially intelligent computer programs. It is related
to the similar task of using computers to understand human intelligence, but AI does not have to confine itself tomethods that are biologically observable. Intelligence is the computational part of the ability to achieve goals in theworld. Varying kinds and degrees of intelligence occur in people, many animals and some machines.
-Intelligence involves mechanisms, and AI research has discovered how to make computers carry out some of themand not others. If doing a task requires only mechanisms that are well understood today, computer programs cangive very impressive performances on these tasks. Such programs should be considered ``somewhat intelligent''.
-AI is not only about simulating human intelligence. We can learn something about how to make machines solve
problems by observing other people or just by observing our own methods. On the other hand, most work in AI
involves studying the problems the world presents to intelligence rather than studying people or animals. AI
researchers are free to use methods that are not observed in people or that involve much more computing thanpeople can do.

Artificial Intelligence (AI)-Examples andApplications…….

Artificial Intelligence (AI)-Examples andApplications…….

Examples include:

Examples include:•
Autonomous Google Car-Technology Readiness Level (TRL) 7, Usefulness Purpose•

Kitchen Robot by Moley Robotics-Technology Readiness Level (TRL) 7, Usefulness Purpose
THE WORLD'S FIRST ROBOTIC KITCHEN
Moley has created the world's first robotic kitchen. Featuring an advanced, fully functional robot
integrated into a beautifully designed, professional kitchen, it cooks with the skill and flair of amaster chef. The prototype was premiered to widespread acclaim at Hanover Messe, theinternational robotics show.
The consumer version set for launch in 2017 will be supported by an iTunes' style library ofrecipes.

Google self-driving cars are designed to navigate safely through city streets.
They have sensors designed to detect objects as far as two football fields away in all directions,
including pedestrians, cyclists and vehicles—or even fluttering plastic shopping bags and rogue
birds. The software processes all the information to help the car safely navigate the road without
getting tired or distracted.

Artificial Intelligence (AI)-Examples andApplications…….

Artificial Intelligence (AI)-Examples andApplications…….

Examples include:

Examples include:•

Insect-like Drones-Technology Readiness Level (TRL) 7, Usefulness Purpose•

One of the current areas of research reportedly being undertaken in the scientific/military field isthe development of micro air vehicles (MAVs), tiny flying objects intended to go places that cannot
be (safely) reached by humans or other types of equipment.
Some efforts in MAV research have involved trying to mimic birds or flying insects to achieve flightcapabilities not attainable through other means of aerial propulsion.

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ALO the Robot Botlr in Aloft Hotels by Savioke-Technology Readiness Level (TRL) 7, Usefulness
Purpose
The robot is approximately 3 feet tall, weighs less than 100 lbs., has a carrying capacity of 2 cubic
feet, and is designed to travel at a human walking pace. It can even travel independently between
floors via the hotel elevator. When Aloft's A.L.O. arrives at the appropriate guest room, it phones
the guest to announce its arrival, delivers the goods and makes its way back to the front
desk. A.L.O. will know when a guest opens the door via an onboard camera. Once the door
opens, A.L.O. will unlock, open its lid and provide instructions through onscreen prompts forguests to remove the item and close the lid.

The Impact and Future of Artificial
Intelligence (AI)………….Pre-Study

Research Investigation Findings in iREX
exhibition hall…… Artificial Intelligence (AI)Specific Examples Studied:•
Robot butlers can provide a specific set of automated skills, and one that could work, literally
around the clock.
•
Imagine if everyone could get around easily and safely, regardless of their ability to drive.
•
Aging or visually impaired loved ones wouldn't have to give up their independence. Time spentcommuting could be time spent doing what you want to do. Deaths from traffic accidents—over
1.2 million worldwide every year—could be reduced dramatically, especially since 94% of
accidents in the U.S. involve human error.
•
Insect Drones can be used as one of the primary military applications envisioned for MAVs is thegathering of intelligence (through the surreptitious use of cameras, microphones, or other types of
sensors); among the more extreme applications posited for such devices is that they may
eventually be used as "swarm weapons" which could be launched en masse against enemy
forces.
•After more than 50 years after robots appeared in specialised manufacturing facilities, theadvancements in automation, sensors and advanced software systems and associated cost
curves mean we are at the point where robots will be seen more and more in the domestic
environment.
•This is an opportunity for people to enjoy very good food, and for a reasonable price.
•
You can download a recipe and reproduce it exactly as a Master Chef would have cooked it,
wherever you are in the world.

Booths Visited:•
FETCH Robotics, Mitsubishi, Rethink Robotics, RT Works, Kawada Robotics, NSK, Softbank Robotics, Tokyo
Metropolitan Industrial Technology Research Institute, Pacific Systems
Summary:•
Overall the average technology readiness level is a 7.6, ranging from 3 to 9. Most technologies utilizing
artificial intelligence have surpassed the design stage and is now an industry comprised heavily of prototype
robots. However, this technology is advancing daily to increase our knowledge of automation. Thisadvancement will help not only industries but hospitals, homes, and transportation as well. Artificial
intelligence decreases the risk of injury and human error as well as helping to create independence among
the elderly and handicapped.

Most Advanced Technologies of
Robots.............3D Printing

3D Printing-Examples andApplications…….

3D Printing Technology

Examples & Applications of 3D printing in Robot Industries:•
What is 3D Printing?
-3D printing or additive manufacturing is a process of making three dimensional solid objects from a digital file. The
creation of a 3D printed object is achieved using additive processes. In an additive process an object is created bylaying down successive layers of material until the entire object is created. Each of these layers can be seen as athinly sliced horizontal cross-section of the eventual object.
The American Society for Testing and Materials (ASTM) group “ASTM F42 – Additive Manufacturing” developed aset of standards that classify the Additive Manufacturing processes into 7 categories according to Standard
Terminology for Additive Manufacturing Technologies.
The 7 categories are:•Vat Photopolymerisation•
Material Jetting•
Binder Jetting•Material Extrusion•
Powder Bed Fusion•
Sheet Lamination•
Directed Energy Deposition••

Medical industry-Technology Readiness Level (TRL) 9, Usefulness Purpose
The outlook for medical use of 3D printing is evolving at an extremely rapid pace as specialists are beginning toutilize 3D printing in more advanced ways. Patients around the world are experiencing improved quality of carethrough 3D printed implants and prosthetics never before seen.
Bio-printing-Technology Readiness Level (TRL) 7, Usefulness Purpose
As of the early two-thousands 3D printing technology has been studied by biotech firms and academia for possible
use in tissue engineering applications where organs and body parts are built using inkjet techniques. Layers ofliving cells are deposited onto a gel medium and slowly built up to form three dimensional structures. We refer tothis field of research with the term: bio-printing.
Automotive industry-Technology Readiness Level (TRL) 9, Usefulness Purpose
Although the automotive industry was among the earliest adopters of 3D printing it has for decades relegated 3d
printing technology to low volume prototyping applications.
Nowadays the use of 3D printing in automotive is evolving from relatively simple concept models for fit and finish
checks and design verification, to functional parts that are used in test vehicles, engines, and platforms. The
expectations are that 3D printing in the automotive industry will generate a combined $1.1 billion dollars by 2019.

The Impact and Future of 3D
Printing………..Pre-Study

Research Investigation Findings in iREX
exhibition hall…… 3-D Printing•

Booths Visited:•
Altech Co. Ltd, Stratasys, Hakuto, Mutoh, J3D, Bonsai Lab
Summary:•
Overall the average technology readiness level is a 7.4, ranging from 5 to 9. 3-D Printing is a valuable tool for
prototyping and manufacturing. The technology allows for a low cost eco-friendly material which can beformed into almost any shape and size. The 3-D Printers are capable of creating entire robot frames,
prosthetics, novelties, and hardware. With this technology industries are able to create complex objects dueto the software’s ability to develop structures which would be otherwise impossible to create with othermethods.

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FutureIt is predicted by some additive manufacturing advocates that this technological development will change thenature of commerce, because end users will be able to do much of their own manufacturing rather than engaging
in trade to buy products from other people and corporations.
3D printers capable of outputting in color and multiple materials already exist and will continue to improve to apoint where functional products will be able to be output. With effects on energy use, waste reduction,customization, product availability, medicine, art, construction and sciences, 3D printing will change the
manufacturing world as we know it.
Services
Not everybody can afford or is willing to buy their own 3D printer. Does this mean you cannot enjoy the possibilitiesof 3D printing? No, not to worry. There are 3D printing service bureaus like
Shapeways, Ponoko and Sculpteo that can very inexpensively print and deliver an object from a digital file thatyou simply upload to their website. You can even sell your 3D designs on their website and make a little money outof it!
There are also companies who offer their services business-to-business. When, for instance, you have anarchitecture practice and you need to build model scales, it is very time consuming doing this the old fashioned
way. There are services where you can send your digital model to and they print the building on scale for you to
use in client presentations. These kind of services can already be found in a lot of different industries like dental,
medical, entertainment and art.
3D Marketplaces
If you don’t have the skills to design your own 3D models, you can still print some very nice objects. 3D
marketplaces such as Pinshape and CGTrader contain 3d model files you can download for a small charge or for
free.

Most Advanced Technologies of
Robots.............Electroencephalography (EEG)
What is EEG?
Electroencephalography (EEG) is an electrophysiological monitoring method to record electricalactivity of the brain. It is typically noninvasive, with the electrodes placed along the scalp, althoughinvasive electrodes are sometimes used in specific applications. EEG measures voltage
fluctuations resulting from ionic current within the neurons of the brain. In clinical contexts, EEG
refers to the recording of the brain's spontaneous electrical activity over a period of time,[1] asrecorded from multiple electrodes placed on the scalp. Diagnostic applications generally focus on
the spectral content of EEG, that is, the type of neural oscillations (popularly called "brain waves")that can be observed in EEG signals.

Electroencephalography (EEG)-Example
and Application……….
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Mind-Controlled Robot Arm-Technology Readiness Level (TRL) 7, Usefulness Purpose :The US Defense Advanced Research Projects Agency (DARPA) presented the achievements it’d had to date inbuilding a robot arm that can be controlled by a human brain. A little over two months later, the agency had
announced at another conference that it’s managed to update the technology to give the wearer the feeling ofactually being able to sense things with the arm.
The robotic arm is connected by wires that link up to the wearer’s motor cortex—the part of the brain that controls
muscle movement—and sensory cortex, which identifies tactile sensations when you touch things. The wires fromthe motor cortex allow the wearer to control the motion of the robot arm, and pressure sensors in the arm thatconnect back into the sensory cortex give the wearer the sensation that they are touching something.
According to the project’s program manager, Justin Sanchez, the team blindfolded the first person connected to
the robot arm, and lightly touched his fingers. He was able to recognize which of his fingers had been touched,even when the team tried to trick him by touching two fingers at once. “He responded in jest asking whether
somebody was trying to play a trick on him,” Sanchez said in a release. “That is when we knew that the feelings he
was perceiving through the robotic hand were near-natural.”The Impact and Future of
Electroencephalography (EEG)…Pre-Study

Technology Readiness Level (pre-study
research) Summary……………….

Specific Examples Studied:•
A quadriplegic might use a house-bound arm to feed herself without having to rely on a human
helper.
•Musicians might be able to eliminate the need for tools and interfaces like sheet music—or evenplaying an instrument—by simply creating music directly with their thoughts.
•
Filters can screen incoming calls of busy mobile phone users by simply monitoring the state of theuser's brain.
•
An object to be created by thought alone—paired with the growing power of the latest 3-D printing
machines.
•
For the disabled, the ability to move about using the power of their minds could be life changing.
Scientists have worked for years on wheelchairs and other devices that could restore mobility tothose who had lost control of their own bodies b•
Human machine interfaces are becoming part of the human body. One new prosthetic evenprovides a sense of "touch" like that of a natural arm, because it interfaces with the wearer's
neural system by splicing to residual nerves in the partial limb.
•
The prosthetic sends sensory signals to the wearer's brain that produce a lifelike "feel," allowing
users to operate it by touch rather than by sight alone. This ability enables tasks many take for
granted, like removing something from inside a grocery bag, and knowing how hard to grip itemswith the prosthetic hand.

1. Artificial Intelligence-Technology Readiness Level 7, Usefulness
Purposes

Impact and Challenges of the Advancementof Technologies in Robots………

Impact and Challenges of the Advancementof Technologies in Robots continued………

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The major challenge for the commercialization of these sci-fi prosthetics is the cost.
Michael McLoughlin is head of the DARPA effort at Johns Hopkins University's Applied
Physics Lab (APL), where the work on Revolutionizing Prosthetics has been under way
since 2006. McLoughlin says that engineers are well on their way to solving the technicalchallenges of building such a thing. Instead, he singles out cost as the main barrier tocommercialization.
Another issue is simply the neuroscience, says NYU neuroscientist and brain-machineinterface researcher Robert Froemke, who is not affiliated with DARPA. "We don't
understand how the brain generates movement signals. We understand that a little bit,particularly in work from animal models, but there's limited data in humans." In other words,
more testing needs to be done on brave research projects like those participating in
Revolutionizing Prosthetics.
Challenge 1. Biological systems can adapt to new environments--not perfectly, they die insome environments, but often they can adapt. Currently our programs are very brittle, andcertainly a program compiled for one architecture cannot run on another architecture. Can
we build a program which can install itself and run itself on an unknown architecture? Thissounds very difficult. How about a program which can probe an unknown architecture froma known machine and reconfigure a version of itself to run on the unknown machine? Stillrather difficult, so perhaps we have to work up to this by making some "blocks worlds"
artificial architectures where we can do this. This might lead to some considerations of how
future architectures might be designed so that software is self-configurable, and then evenperhaps self-optimizing.

2. 3D Printing-Technology Readiness Level 9, Usefulness and Novelty
Purposes
3. Electroencephalography (EEG)-Technology Readiness Level 7,
Usefulness Purposes

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Minsky (1967) was foundational in establishing the theory of computation, but after Hartmanis (1971) there has been afixation with asymptotic complexity. In reality lots of problems we face in building real AI systems do not get out of hand interms of the size of problems for individual modules--in particular with behavior-based systems most of the submodules need
only deal with bounded size problems. There are other ways theory could have gone. For instance one might try to come up
with a theory of computation based on how much divergence there might be in programs given a one bit error in either the
program or data representation. If theory were based on this fundamental concern we might start to understand how to makeprograms more robust.
Recent work with evolutionary system has produced some tantalizing spectacular results, e.g., Sims (1994). But it is hard toknow how to take things from successes and apply them to new problems. We do not have the equivalent of the Perceptron
book (Minsky and Papert 1969) for evolutionary systems. (Note that these evolutionary systems are much more that straight
genetic algorithms as there is both a variable length genotype and a morphogenesis phase that produces a distinctly
different phenotype.) We need such a new book of mathematics so that we understand the strengths and weaknesses of thisexciting new approach.
We have been living with the basic formalizations made by McCulloch and Pitts (1943) for over fifty years now. Their
formalization included that the activity of the neuron is an "all-or-none" process, that a certain fixed number of synapses must
be excited within the period of latent addition in order to excite a neuron at any time, and this number is independent of thesynapses' previous activity and position on the neuron, that the only significant delay within the nervous system is synaptic
delay, that the activity of any inhibitory synapse absolutely prevents excitation of the neuron at that time, and that thestructure of the net does not change with time. With the addition of changing synaptic weights by Hebb (1949) we prettymuch have the modern computational model of neurons used by most researchers. With 50 years of additional
neuroscience, we now know that there is much more to real neurons. Can newer models provide us with new computational
tools, and will they lead to new insights to challenge the learning capabilities that we see in biological learning?
Over time we become trapped in our shared visions of appropriate ways to tackle problems, and even more trapped by ourfunding sources where we must constantly justify ourselves by making incremental progress. Sometimes it is worthwhile
stepping back and taking an entirely new (or perhaps very old) look at some problems and to think about solving them in new
ways. This takes courage as we may be leading ourselves into different sorts of solutions that will for many years havepoorer performance than existing solutions. With years of perseverance we may be able to overcome initial problems with
the new approaches and eventually leapfrog to better performance. Or we may turn out to be totally wrong. That is where thecourage comes in.

Impact and Challenges of the Advancementof Technologies in Robots continued………
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Despite some early misgivings (Selfridge 1956) back when chess playing programs
had search trees only two deep (Newell et al. 1958), our modern chess programs
completely rely on deep search trees and play chess not at all like humans. Can webuild a program that plays chess in the way that a human plays? If we could, thenperhaps we could prove how good it was by getting it to play GO--tree search justcannot cut it with GO.
All of the competitive speech understanding systems today use hidden Markov
models. While trainable, these systems have some unfortunate properties. They havemuch higher error rates than we might desire, they require some restriction indomain, and they are often inordinately sensitive to the choice of microphone. It
seems doubtful that people use HMM's internally (even if one doesn't believe thatgenerative grammars are the right approach either). Can we build a speech
understanding system that is based on very different principles?
We live in an environment where we make extensive use of non-speech sound cues.
There has been very little work on noise understanding. Can we build interesting
noise understanding systems?
Can we build a system by evolution that is better at a non-trivial task than anythingthat has been built by hand?

The End

Waialua Robotics Program
Waialua High & Intermediate School (Waialua, HI)