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GeckoSystems Begins Licensing Discussions With Publicly Traded Robotics Co.
(Market Wire Via Acquire Media NewsEdge) CONYERS, GA -- (MARKET WIRE) -- 02/08/10 --
GeckoSystems Intl. Corp. (PINKSHEETS: GCKO) (http://www.geckosystems.com/) -- announced today that they have entered into substantive technology licensing
discussions with a U.S. robotics company. GeckoSystems is a dynamic leader
in the emerging mobile robotics industry revolutionizing their development
and usage with "Mobile Robot Solutions for Safety, Security and
Service?."
Martin Spencer, President/CEO of GeckoSystems, stated: "As all of us here at
GeckoSystems are excited about this development, due to the nature of the
upcoming discussions, I feel it is in the best interest of all parties
involved to withhold the name of this publicly traded company at this time.
The potential outcome(s) of it is something that has been in the works for
several years and is now coming to what looks to be an extraordinarily
profitable culmination. I believe their interest in us is due to not only
our flagship product, the automatic self navigation software, GeckoNav?,
but also the reality that we have a complete multitasking personal robot,
the CareBot?, with verbal interaction capabilities, GeckoChat?, and
the ability to routinely follow a designated family member with
GeckoTrak?."
The cost saving benefits of GeckoSystems' suite of mobile robot technologies
will generate additional multiple revenue streams for GeckoSystems in the
form of licensing, royalties, training, and sales of various software and/or
hardware systems and/or subsystems beyond manufacturing and distribution of
GeckoSystems' coming product line of mobile service robots. The CareBot?
is their first product, now in in home evaluation trials, to be realized
from their suite of proprietary technologies.
"Hence our strongly held belief that given our extraordinarily efficient and
very robust AI navigation engine, and its portability, we expect GeckoNav to
also be important in other large markets such as professional healthcare,
education, commercial security, public safety, agriculture and defense. Our
basebot technologies, such as GeckoNav, are not only relevant for consumer
markets, but also several other business-to-business markets for improved
ROI for our investors," concluded Spencer.
GeckoNav's Core Capabilities:
1. Subsumptive software architecture enabling cognizant navigation for
unexpected obstacle (static or dynamic) avoidance while "on path" with the
ability to resume path following.
2. Sensor fusion technology such that the GeckoNav is sensor loving. By
utilizing multiple sensor systems (like a blind man listening and counting
steps while using a cane uses two senses -- tactile and hearing -- to
routinely navigate known and unknown environments) the GeckoNav's AI
software architecture enables differing, high-count sensor systems synergy.
3. Short term AI memory software such that GeckoSystems' proprietary sensor
fused, scanning CompoundedSensorArray may be fully utilized. Consequently,
total cost for sensor systems is dramatically reduced.
4. Emergent behaviors expression (which are not pre-programmed) such as the
left/right routine when encountering a dynamic obstacle that moves to the
same side that the robot has chosen to use to avoid the now confounding
obstacle. The robustness of this emergent behavior is apparent as the robot
finally, after several left/right attempts, succeeds in avoiding the dynamic
obstacle, and resumes path.
The resultant level of mobile autonomy can be likened to that of a "blind
man with a cane in his own home" or "loose crowd capable." All GeckoNav
source code is in C++ and is not hardware or OS centric.
Some Fundamental Issues of Automatic Self-navigation in Dynamic
Environments
Background:
For any Mobile Service Robot (MSR) to have probable hope of utility, it must
have the intrinsic and timely ability to avoid unforeseen, dynamic obstacles
and still reach its desired endpoints or physical locations. Many MSR
prototypes are limited by their navigation software architecture.
Historically, MSR architectures have been based on either a pre-set path
following technique, where the sensors are only used to detect failure of
the preprogrammed path, or they have used a purely reactive technique that
has no concept of the larger world that the MSR inhabits and cannot be used
for useful tasks.
The path-following techniques suffer from being unable to adapt to changing
conditions quickly or smoothly. The MSR basically travels blind until it is
about to hit something, and once it has detected an obstacle, the resulting
decisions required are very complex. As a result, the environment must be
highly structured to avoid confusing the MSR so that simple decisions will
suffice or a lot of computing power must be available to maintain and
compute path alternatives. Requiring a highly structured environment reduces
the usefulness and flexibility of such a MSR in a human environment. In
addition, the need for a lot of processing power makes MSRs really expensive
and their useful "on" time very short due to the power required for the
"high clock" CPU or PC typically on board.
Further, the purely reactive architectures suffer from having little sense
of past events, future goals, or of even where exactly the MSR is within the
world. Typically such MSRs have no memory of the world that they have
traveled and "live" only instant-to-instant. They may reach a particular
destination, but it is by pure chance and the MSR will not be able to
recognize that it has reached the desired destination without providing a
modified environment (e.g. beacon techniques such as the legendary Arctec
Systems' "Gemini," Evolution Robotics ER-1 and others). In its pure form,
something seen in many toy robots, this technique is almost useless for true
automatic self-navigation or tasks in a dynamic human environment. This kind
of MSR is typically characterized by its use of binary IF-THEN rules like
"If bumped left then turn right." Such an architecture does not scale for
the multiple sensors required for Cognizant Navigation. Cognizant Navigation
is the ability to find locations repeatedly upon request without hitting
unexpected obstacles.
Cognizant Navigation is a non-trivial problem that has a number of facets.
There must be enough sensor information of the right kind to not hit large
obstacles such as walls, furniture, and people. There must also be enough
sensor information to avoid smaller obstacles such as toys. Furthermore, the
navigation engine must be able to react to quick local changes without
losing track of its task. The MSR must also have a memory of where it is
within the world and be able to repeatedly find locations within that world
even if there are unexpected obstacles. This means that there must be enough
processing power and RAM to accomplish this while still having enough
battery life to stay active for many hours while performing useful tasks
like vacuuming or carrying more than a trivial sized load. These important
capabilities are the basic, required foundation for useful MSRs in a human
environment. Until the CareBot, almost all consumer MSRs have fallen short
in one or more of these areas.
Cognizant Navigation is much more than the simple reactive, bump-turn mobile
robot behaviors seen in most traditional, or legacy mobile robots. Such a
robot may reach the goal, but isn't "aware" that it is attempting to reach
that goal and can't recognize it when located. Other legacy mobile robots
blindly follow line segment paths like virtual train tracks and may be
"aware" that they are trying to reach a goal, but they have problems when
reacting to new situations that require deviation from the planned route due
to their limited sensors and available CPU power. Typically, these robots
cannot sense obstacles until they actually run into them!
Are these MSRs cognizant? Cognizant means to be aware or have conscious
knowledge. The word "aware" implies the MSR remembers where it is, where it
was, where it is "supposed" to be going, as well as being aware of immediate
changes in the environment that may require a response. Humanlike short term
and long memory management, along with enough sensor information, is the key
to resolving this problem. Your existing PC has the raw computing power,
memory, and data storage needed for robust personal MSR cognizant
navigation, scheduling of areas to be vacuumed, and much, much more.
GeckoSystems's GeckoNav is different. Its Biological Hierarchical
Architecture provides the benefits of both control and reaction within a
single framework without the disadvantages of either technique alone. As a
result, it is able to respond quickly and intelligently to short-term
navigation situations while still providing the ability to guide the MSR
toward accomplishing useful tasks within a map of the world that the MSR
maintains. It turns out that this approach is synergistic and reduces the
complexity of trying to "force fit" either of the other traditional
solutions to solve the whole problem.
Biological Hierarchical Architecture is a GeckoSystems' proprietary MSR
navigation software scheme incorporating several advanced artificial
intelligence (AI) methods such that together vote on the best solution. It
should be noted that "sufficient" sensors for navigating a home environment
while avoiding unexpected obstacles is a critical prerequisite.
Sensors - Why Other MSRs Bump into Walls, Chairs, Tables, etc.
Many available MSRs are limited by their sensor count, position and/or
interpretation strategy. MSR sensors such as bump switches, feelers, and
whiskers have the problem that they cannot sense their environment without
actually colliding with the world. Fixed single sonar and infrared distance
(IR) range finders are an improvement, but individually they give very
little information about the surrounding world. They may help avoid running
into an obstacle directly in front of the MSR in one narrow direction, but
they aren't very useful in helping the MSR navigate. There are too many
directions from which unseen problems can approach, and even if the obstacle
is detected, it is practically impossible tell the true extent of the
obstacle and what the response should be from that single data point.
Even having many different kinds of these sensors does not necessarily solve
this problem. The MSR must be able to assess the current space around the
MSR to enable robust navigation, and to do that the MSR must have enough
information of the right kind, not just many arbitrary sensors. Expensive
research MSR manufacturers understand this need, and solve this problem
through a very costly array of multiple sonar and IR sensors or even more
expensive machine vision systems and/or laser rangefinders interpreted by
either CPU intensive computations, or by quicker neural nets that can be
easily over trained and become brittle in their ability to reliably discern
fixed and/or moving, unforeseen obstacles.
GeckoSystems's solution to this problem uses high-data, low cost fixed
ultrasonic rangefinders (sonars) and scanning IR sensors in an array called
the CompoundedSensorArray?. The CSA can image the surrounding space in
250-275 different directions, not just one single direction like a single
fixed sensor. This is actually more advanced than most research MSRs in this
respect, which in contrast can generally sense between only 7 to 16 unique
obstacle positions on the forward half of the MSR. This is an increase in
resolution of 15 to 40 times over such MSRs! The reason for this is that
such MSRs tend to assume and operate in fairly structured environments, like
offices, empty campus hallways and contest mazes and as a result encounter
fewer challenges in their environments. In contrast, GeckoSystems' basebot
technologies have been designed and tested for typical home environments,
which many consider to be the most challenging of all, from the beginning.
About GeckoSystems International Corporation:
Since 1997, GeckoSystems has developed a comprehensive, coherent, and
sufficient suite of hardware and software inventions to enable a new type of
home appliance (a personal companion robot) the CareBot?, to be created
for the mass consumer marketplace. The suite of primary inventions includes:
GeckoNav?, GeckoChat? and GeckoTrak?.
The primary market for this product is the family for use in eldercare, care
for the chronically ill, and childcare. The primary distribution channel for
this new home appliance is the thousands of independent personal computer
retailers in the U.S. The manufacturing infrastructure for this new product
category of mobile service robots is essentially the same as the personal
computer industry. Several outside contract manufacturers have been
identified and qualified their ability to produce up to 1,000 CareBots per
month within four to six months.
The Company is market driven. At the time of founding, nearly 12 years ago,
the Company did extensive primary market research to determine the
demographic profile of the early adopters of the then proposed product line.
Subsequent to, and based on that original market research, they have
assembled numerous focus groups to evaluate the fit of the CareBot personal
robot into the participant's lives and their expected usage. The Company has
also frequently employed the Delphi market research methodology by
contacting and interviewing senior executives, practitioners, and
researchers knowledgeable in the area of elder care. Using this factual
basis of internally performed primary and secondary market research, and
third party research is the statistical substance for the Company's sales
forecasts.
Not surprisingly the scientific statistical analyses applied revealed that
elderly over sixty-five living alone in metropolitan areas with broadband
Internet available and sufficient household incomes to support the increased
costs were identified as those most likely to adopt initially. Due to the
high cost of assisted living, nursing homes, etc. the payback for a
CareBot? is expected to be only six to eight months while keeping elderly
care receivers independent, in their own long time homes, and living longer
due to the comfort and safety of more frequent attention from their loved
ones.
The Company's "mobile robot solutions for safety, security and service?"
are appropriate not only for the consumer, but also professional healthcare,
commercial security and defense markets. Professional healthcare require
cost effective, timely errand running, portable telemedicine, etc. Homeland
Security requires cost effective mobile robots to patrol and monitor public
venues for weapons and WMD detection. Military users desire the elimination
of the "man in the loop" to enable unmanned ground and air vehicles to not
require constant human control and/or intervention.
The Company's business model is very much like that of an automobile
manufacturer. Due to the final assembly, test, and shipping being done based
on geographic and logistic realities; strategic business-to-business
relationships can range from private labeling to joint manufacturing and
distribution to licensing only.
Several dozen patent opportunities exist for the Company due to the many
innovative and cost effective breakthroughs embodied not only in GeckoNav,
GeckoChat, and GeckoTrak, but also in additional, secondary systems that
include: GeckoOrient?, GeckoMotorController?, the
GeckoTactileShroud?, the CompoundedSensorArray?, and the
GeckoSPIO?.
The present senior management at GeckoSystems has over thirty-five years
experience in consumer electronics sales and marketing and product
development. Senior managers have been identified for the areas of
manufacturing, marketing, sales, and finance.
While GeckoSystems has been in the Development Stage, the Company has
accumulated losses to date in excess of six million dollars. In contrast,
the Japanese government has spent one hundred million dollars in grants (to
Sanyo, Toshiba, Hitachi, Fujitsu, NEC, etc.) over the same time period to
develop personal robots for their eldercare crisis, yet no viable solutions
have been developed.
By the end of this year, the Company plans to complete productization of its
CareBot offering with the introduction of its fourth generation personal
robot, the CareBot 4.0 MSR. The Company is the first personal robot
developer and manufacturer in the world to begin in-home eldercare
evaluation trials.
What Does a CareBot Do for the Care Giver?
The short answer is that it decreases the difficulty and stress for the
caregiver that needs to watch over Grandma, Mom, or other family members
most, if not much, of the time day in and day out due to concerns about
their well being, safety, and security.
But, first let's look at some other labor saving, automatic home appliances
most of us use routinely. For example, needing to do two or more necessary
chores and/or activities at the same time, like laundering clothes and
preparing supper.
The automatic washing machine needs no human intervention after the dirty
clothes are placed in the washer, the laundry powder poured in, and the
desired wash cycle set. Then, this labor saving appliance runs automatically
until the washed clothes are ready to be placed in another labor saving home
appliance, the automatic clothes dryer. While the clothes are being washed
and/or dried, the caregiver prepares supper using several time saving home
appliances like the microwave oven, "crock" pot, blender, and conventional
stove, with possible convection oven capabilities.
After supper, the dirty pots, pans, and dishes are placed in the automatic
dishwasher to be washed and dried while the family retires to the den to
watch TV, and/or the kids to do homework. Later, perhaps after the kids have
gone to bed, the caregiver may then have the time to fold, sort, and put up
the now freshly laundered clothes.
So what does a CareBot do for the caregiver? It is a new type of labor
saving, time management automatic home appliance.
For example, the care giver frequently feels time stress when they need to
go shopping for 2 or 3 hours, and are uncomfortable when they have to be
away for more than an hour or so. Time stress is much worse for the
caregiver with a frail elderly parent that must be reminded to take
medications at certain times of the day. How can the caregiver be away for
3-4 hours when Grandma must take her prescribed medication every 2 or 3
hours? If the caregiver is trapped in traffic for an hour or two beyond the
2 or 3 they expected to be gone, this "time stress" can be very difficult
for the caregiver to moderate.
Not infrequently, the primary caregiver has a 24 hour, 7 days a week
responsibility. After weeks and weeks of this sometimes tedious, if not
onerous routine, how does the caregiver get a "day off?" To bring in an
outsider is expensive (easily $75-125 per day for just 8 hours) and there is
the concern that medication will be missed or the care receiver have an
accident requiring immediate assistance by the caregiver, or someone they
must designate. And the care receiver may be very resistant to a "stranger"
coming in to her home and "running things."
So what is it worth for a care receiver to have an automatic system to help
take care of Grandma? Just 3 or 4 days a month "off" on a daylong shopping
trip, a visit with friends, or just take in a movie would cost $225-500 per
month. And that scenario assumes that Grandma is willing to be taken care of
by a "stranger" during those needed and appropriate days off.
So perhaps, an automatic caregiver, a CareBot, might be pretty handy, and
potentially very cost effective from the primary caregiver's perspective.
What Does a CareBot Do for the Care Receiver?
It's a new kind of companion that always stays close to them enabling family
and friends to care for them from afar. It tells them jokes, retells family
anecdotes, reminds them to take medication, reminds them that family is
coming over soon (or not at all), recites Bible verses, plays favorite songs
and/or other music. It alerts them when unexpected visitors, or intruders
are present. It notifies designated caregivers when a potentially harmful
event has occurred, such as a fall, fire in the home, or simply been not
found by the CareBot for too long. It responds to calls for help and
notifies those that the caregiver determined should be immediately notified
when any predetermined adverse event occurs.
The family can customize the personality of the CareBot. The voice's cadence
can be fast or slow. The intonation can be breathy, or abrupt. The voice's
volume can range from very loud to very soft. The response phrases from the
CareBot for recognized words and phrases can be colloquial and/or unique to
the family's own heritage. The personality can range from brassy to timid
depending on how the care giver, and others appropriate, chooses it to be.
Generally, the care receiver is pleased at the prospect of family being able
to drop in for a "virtual visit" using the onboard webcam and video monitor
for at home "video conferencing." The care receiver may feel much more
needed and appreciated when their far flung family and friends can "look in"
on them anywhere in the world where they can get broadband internet access
and simply chat for a bit.
Why is Grandma really interested in a CareBot? She wants to stay in her
home, or her family's home, as long as she possibly can. What's that worth?
Priceless. Or, an average nursing home is $5,000 per month for an
environment that is too often the beginning of a spiral downward in the care
receiver's health. That's probably $2-3K more per month for them to be
placed where they really don't want to be. Financial payback on a CareBot?
Less than a year. Emotional payback for the family to have this new
automatic care giver? Nearly instantaneous.
Safe Harbor:
Statements regarding financial matters in this press release other than
historical facts are "forward-looking statements" within the meaning of
Section 27A of the Securities Act of 1933, Section 21E of the Securities
Exchange Act of 1934, and as that term is defined in the Private Securities
Litigation Reform Act of 1995. The Company intends that such statements
about the Company's future expectations, including future revenues and
earnings, technology efficacy and all other forward-looking statements be
subject to the Safe Harbors created thereby. The Company is a development
stage firm that continues to be dependent upon outside capital to sustain
its existence. Since these statements (future operational results and sales)
involve risks and uncertainties and are subject to change at any time, the
Company's actual results may differ materially from expected results.
Contact:
GeckoSystems Intl. Corp.
http://www.geckosystems.com/
Main number: 1-866-CAREBOT (227-3268)
International: +1 678-413-9236
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Thrupoint is committed to providing unsurpassed technology and consulting services to leaders in the networked economy. We deliver value to our partners by giving them access to our award winning Ubiquity communications platform and NGIC Applications. Our ecosystem is at the ready to help propel the sales of our partners with best-in-class technology solutions, combining strategic resources to deliver high-value competitive advantage to our clients.
Thrupoint is committed to providing unsurpassed technology and consulting services to leaders in the networked economy. We deliver value to our partners by giving them access to our award winning Ubiquity communications platform and NGIC Applications. Our ecosystem is at the ready to help propel the sales of our partners with best-in-class technology solutions, combining strategic resources to deliver high-value competitive advantage to our clients.
