We’ve already seen it dance, sing and read minds. The new ASIMO is faster, skinnier and more ergonomic than any Robot ever made. It can walk, run backward and forward, run on a single leg, twist and rip the the bottle caps and what not.  In fact, Honda claims that its bot is now less “automated” than it is “autonomous” — all thanks to new behavior control technology that allows it to move and make decisions on its own, independent of human operators.

It can rapidly process information about its environment, and undertand the dynamics of the situation before making the next move. ITs even smart enough to combine long- and short-term sensor data to predict human movements and automatically recognize voices or gestures.This is what makes it co-exist with Humans, naturally.

Structure wise, its more flexible and capable. It can now run at 9 km/h. Its hands are now more dexterous than ever, thanks to new independent finger control functions, this allows it to execute delicate tasks, with ease.

Checkout more Robotics posts.

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Festo, a bionic design company, has come up with a breakthrough — World’s first Robot that Flies like an Actual Bird. The company has invested a lot of time studying the natural flight of a bird. The wingspread, the angles, the thrust, the art and engineered all of them to a masterpiece which they call it as “SmartBird“.

SmartBird is an ultralight but powerful flight model, weighing just 450grams, including batteries. This bionic technology bird can start, fly and land autonomously – with no additional drive mechanism. It can twist at specific angles, jut like a bird can. Active articulated torsional drive unit in combination with a complex control system attains an unprecedented level of efficiency in flight operation.

SmartBird @ TED

SmartBird is energy efficient at 25 wattts during take-offs and nearly 16watts during normal flying. However, the plan is to make it even more efficient. So far, it had been made possible with minimal use of materials and the extremely lightweight construction with components like Carbon-fiber.

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iRobot has developed a new series of autonomous Robots called Ava that are equipped with array of sensors like 3D cameras (like Kinect), scanning laser, ultrasonic transducers, driven by omnidirectional wheels. They are powered by base hosts batteries, motors, as well as electronics and supports a telescopic mast that carries a pod containing touch ribbons, speakers, and a microphone.

iRobot Ava is based on Intel Core-based computers with a tilt capable head on top of with is basically an Android tablet. Ava is capable of roaming around by studying the ambiance, even with people walking around, it can save itself from actually hitting anyone. The onboard computer does all the computations to let it walk without trouble.

Google and iRobot have worked together and created APIs that allow Android developers to write apps — from telepresence to roaming testimonials — that control Ava wirelessly from the docked tablet. This would bring new projects which combine the power of robotics and Android devices. Its hard to talk about prices and timelines at the moment, but they are about to hit the market and developers sometime later this year. Stay tuned.

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Angry Birds, for the first time has invaded the Robotics. Of course they dont feel the love, but they surely can play the world’s most popular game on mobile.

OptoFidelity has now been developing robotic test automation products for a while and it was one day when they came up with a whacky idea of making robots playing games on mobile.

The purpose is of course not time wasting or entertainment, but its specifically designed to create an expert (or ideal) user to automate all kinds of Real-world testing for mobile applications. And when its put into action, its perfection.

These Robots are are based on RealTime systems designed using FPGAs. They are powered by NI products like NI CompactRIO, NI single-board RIO, NI LabVIEW. This application allows customers create their own driver to do different things, without modifying the core software. The customized driver would work with any hardware or application on any platform.

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Morgan Quigley’s low-cost Robot possess 7 degree-of-freedom (7-DoF). It possess a series elastic actuator (SEA) arm that costs way under $5,000  The hand possess shape deposition manufacturing (SDM) that gives it  reflexes to catch flying (tossed) balls.

Morgan calls it A Low-Cost Compliant 7-DOF Robotic Manipulator [PDF] that costs just $4135. The arm is made from lasercut plywood, and is powered by four stepper motors in the base and three small dynamixel servo motors in the lower arm. This is done via rubber tubes that get squished between two plates, as can be seen in the video. The arm is pretty light that makes it human-safe. The arm moves at 1.5m/s carrying a 2kg payload. The arm is used to demonstrate pancake cooking (pouring batter, flipping pancakes), using the intrinsic compliance of the arm to aid in interaction with objects.

The mechanism of catching the ball is based on inputs taken from multiple sensors. It uses accelerometers and magnetometers to detect the wearer’s pose. It then calculates the location of the thrower’s hand and inverse kinematics (tracking trajectory) are used to get the robot’s gripper to track that location. The robot is powered by the Robot Operating System (ROS).

Watch the Stanford’s creation in action:

Rollin Justin Robot, a much faster and mature version based on similar concept

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AI

IBM’s Watson has blazed the news when the system played Jeopardy, showcasing the greatest advancements in AI. Prior to that IBM was famous for the Deep Blue, a chess playing Robot, which took a brute-force approach, relying on a giant opening book and sheer computational power to search the game tree, rather than the intuitive approach apparently taken by human players.

In computer science, we often get to see a large number of algorithms that deal with making decisions. The one being used here for Jeopardy is Question Answering (QA), which is part of algorithm called Information Retrieval (IR). IR helps in retrieval of  relevant information or documents from a store (which can be wikis), while QA specifically deals with returning information in response to natural language questions (who, where, when, what, etc.).

On one side where QA goes focuses on answering specifically (just a word or phrase), on the other side IR commonly returns whole documents (as search engines do). IBM calls such a combination of algorithm : DeepQA.

“DeepQA”, Davidian explained, “scales out with and searches vast amounts of unstructured information. Effective execution of this software, corresponding to a less than three second response time to a Jeopardy! question, is not just based on raw execution power. Effective system throughput includes having available data to crunch on. Without an efficient memory sub-system, no amount of compute power will yield effective results. A balanced design is comprised of main memory, several levels of local cache and execution power. IBM’s POWER 750’s scalable design is capable of filling execution pipelines with instructions and data, keeping all the POWER7 processor cores busy. At 3.55 GHz, each of Watson’s POWER7 on-chip bandwidth is 500 Gigabytes per second. The total on-chip bandwidth for Watson’s 360 POWER7 processors is an astounding 180,000 Gigabytes per second!”

The algorithms used to compute the answers are far more complex than normal AI used in Robots. It can be considered as complex as a search engine itself which actually makes decisions. The paper (Ferucci et al 2010, AI magazine), outlines Watson’s approach to Question Answering in detail. It’s 20 pages long, but it’s not incredibly technical, highly recommended for everyone who have the passion.

The machine is named after Thomas J Watson, the founder of IBM.

If you want to succeed, double your failure rate - Thomas J. Watson

The paper begins with acknowledgements of the complexity of the problem and the scope:

“we appreciate that this challenge alone does not address all aspects of QA and does not by any means close the book on the QA challenge the way that Deep Blue may have for playing chess. However, note that while the Jeopardy! game requires that answers are delivered in the form of a question …  this transformation is trivial and for purposes of this paper we will just show the answers themselves”

How Watson is able to Answer in Jeopardy

• When it starts, Watson patiently hears to the question and then figures out answer within a span of 1-3 seconds. The category becomes the core fact for answering the question —  determining the domain of the answer.
• Watson heavily relies on clues & sub-clues. When the clue contains more than a single statement, Watson decides to break it down into subclues. The next step is to identify ‘what kind’ of answer the is being looked for. Its being called Lexical Answer Type (LAT) – Algorithm that helps figuring out which word among the clues represents the required answer. e.g if the question being asked is like “What was the year in history …”, the Lexical Answer Type is ‘year’. However, its really tough to for watson when the question has more pronouns than nouns. “If this is like it, how would that …”. Its easy to lose the context for an Artificial Intelligence engine.
• If all had been well so far, Watson knows the type of the answer it is looking for (year, city, singer), one or more clues relating to the answer, and the category the clue is in. It then searches in its repository for answers — no it doesn’t google search for the answer, as we know, its not answering engine. Apart from that, Jeopardy restricts access to internet, as per the game’s rules. So instead, the DeepQA system builds a large database of web documents which are then stored and searched offline during the live Jeopardy game. It looks for Q&A, encyclopedias, etc as the base to generate web searches used to retrieve pointers to relevant web snippets. These web snippets, together with the initial resources and many other downloadable knowledge bases (dbpedia, freebase, etc) form the “extended corpus” that is Watson’s knowledge base.
• The next step is to analyze the clue further in order to find out how to search the knowledge base. The question analysis section involves intensive Natural Language Processing techniques. The clue fragments are parsed, first syntactically and then semantically, to extract a logical form. The semantic roles in the clue are identified. Semantic role labeling is a major breakthrough in NLP, giving us algorithms that can identify the type of the subject and object in a parsed sentence.
• Coreference resolution detects which entities pronouns refer to, named entity recognition detects terms that are proper nouns referring to people or organizations, relation extraction identifies the parts of the clue that make up predicates or relations between nouns or entities in the clue.
• The process of searching the extended corpus is divided into two steps – at first the focus is on recall – the system generates a bulk of answers in the hope that the correct answer is somewhere in this list. This is done by querying its corpus in varied ways ( using reverse algorithms like Lucene and SPARQL), and returning small snippets of text and individual candidate answers. This list of possible answers is then weighted based upon some additional standalone algorithms, which employs computational lingusitics techniques to examine a particular aspect of the answer. This is actually much tougher and unclear. IBM didn’t explain the aspect in detail.
  “Each of the scorers implemented in Watson, how they work, how they interact, and their independent impact on Watson’s performance deserves its own research paper.”
• The information range and variation collected at this stage is sky-high. There are various components then come into play next — e.g. a component that can compare dates and times,a component for figuring out geographic coordinates, a component for matching the syntactic form of the clue with passages retrieved from web documents, and other scorers that can influence the confidence judgement for a particular answer. Watson tries to be as precise as possible, and it decides the confidence in the answer, based upon the above mentioned components. If its not absolutely sure, it might skip answering.
• Hardware & OS: Watson’s hardware is equally complex. Its powered by lots of parallel computation using Hadoop, which is managed using UIMA. Watson is based on the IBM POWER7 750 in a standard rack mounted configuration. It can run AIX, IBM’s house-brand Unix; IBM I; and Linux. To compete on Jeopardy Watson is running Novell’s SUSE Linux Enterprise Server. IBM didn’t go into detail of the hardware, but its based upon their modern supercomputer engine.

Watson is made up of ninety IBM POWER 750 servers, 16 Terabytes of memory, and 4 Terabytes of clustered storage. Davidian sontinued, “This is enclosed in ten racks including the servers, networking, shared disk system, and cluster controllers. These ninety POWER 750 servers have four POWER7 processors, each with eight cores. IBM Watson has a total of 2880 POWER7 cores.”

Apart from the original paper, there’s one more paper that conceptualizes Large Scale Relation Detection . The paper describes methods for detecting relations between entities in a large corpus (over a billion words of text). This makes most of the things more clearer discussing how patterns of words in text such as “appeared together at the premier of “ can be used to predict other, more useful relations like “co-star in”.  In order to get it to work, there is a need for a large number of built-in, detailed relations between concepts that can be populated using patterns of words in text.

Given the multitude of AI components interacting to solve all the little tasks that must be accomplished to parse a question and relate it to knowledge gained from previously seen documents, it really is Rocket science.

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Actroid is one of the best examples that showcased how Robotics can effectively mimic humans, as they have evolved the tech over last decade. Their current iteration of Actroid is better known as Actroid-F, looks like a  humanoid robot that can mock the operator’s facial expressions and head movements with accuracy seen never before.

Actroid-F is characterized by expressive engine, and one that can reproduce such a laugh and toothy smile, naturally. She can easily trace the movement based upon facial image recognition, which includes gestures like  such as nodding or shaking head.

During the builtup, it achieved significant cost reduction by about one third of the minimum necessary to narrow the degrees of freedom than Akutoroidoshirizu conventional remote control.

During the video she acts “as an observer in hospitals to gauge patient reactions.” She amazes us with real-life facial expressions, watch the video after the break:

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Intel is building the car at its research headquarters which would record Car’s dynamic characteristics like speed, steering and braking along with video footage from inside and outside the vehicle and then like it opr not, will send the data to police and insurance companies in the event of an accident making it easier to determine the cause of car crashes and identify the person responsible.

Apart from the objectional side, Intel is building the technology that will transform cars into smart vehicles that use AI to detect dangers on the road their criticality and even Override the Driver in case of Risky driving. The cars will also be able to track the location of surrounding vehicles and alert drivers if they get too close or try to change lanes when another vehicle is in their blind spot. Using the LED rear and head lights found in most modern cars, the car is able to track the location of other vehicles and display them on a satellite navigation map.

The concept is not new, its been there for a decade, but Intel could be the first one to make it commercial by developing cars that are permanently connected to the internet and vehicles talk to each other over wireless connections thereby smelling dangers and take appropriate actions on both parties.

Taking it further, camera systems can recogonise street signs, consider the situation and take a smart move e.g. it can take over control of a car if the motorist tries to drive the wrong way up a one-way street, or tries to drive fast on a hilly road that has lower speed limit. If you think the drivers are the sole beneficiaries, you are  probably wrong. Onboard sensors will also be able to detect pot holes in the road and report their location to road maintenance authorities as the car is moving.

In addition, Motorists will also be able to use their mobile phone or computer lock and unlock their car remotely, turn on the alarm and even start the engine to warm it up in the morning.

When ?

No doubt, we’ve seen so many of such projects failing in the past. Will this one work? If yes, How soon can we see them on roads?

Intel has been in discussions with car manufacturers about putting the technology into new vehicles. Justin Ratner, the director of Intel Laboratories and chief technology officer, said:

“We are looking at a whole range of enhancements that will improve the driving experience, safety and security of vehicles.The intelligent vehicle is what we are talking about here. Once a car is connected, more or less on a continuous basis, all sorts of interesting possibilities present themselves. We have talked to highway maintenance departments about using sensors that are already in cars to report the GPS coordinates for pot holes in the road to the maintenance department.”

“Insurance companies are always looking at new in car technology. A system like this could certainly help speed up the process of determining the cause and responsibility of an accident. Any system would have to not increase the cost of repairing vehicles though, to ensure that motorists see a fall in their insurance bills.”

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Rockets like the one in this RR-1 prototype lander, recently outfitted with a Guidance Embedded Navigator Integration Environment (GENIE) system to let the craft safely descend to the lunar surface.

NASA has put the whole system to the test, to calculate and interpret  complex algorithms necessary to process volumes of data from the laser altimeter, GPS and inertial sensors, and quickly enough to steer the rocket engine approriately, and surprisingly the first test seemed to work.

Its first solo flight in an inspiring, flame-filled video follows:

The Mission

NASA’s Quote:

Project M is a proposed project to land an operational humanoid robot on the moon in 1000 days (M is the Roman numeral for 1000). The humanoid will travel to the moon on a small lander fueled by green propellants, liquid methane and liquid oxygen. It will perform a precision, autonomous landing, avoiding any hazards or obstacles on the surface. Upon landing the robot will deploy and walk on the surface performing a multitude of tasks focused on demonstrating engineering tasks such as maintenance and construction; performing science of opportunity (i.e. using existing sensors on the robot or small science instruments); and simple student experiments.

The mission is about inspiration, streamlining agency practices and processes and using unconventional partnerships, and building a workforce and demonstrating technologies to enable the continuation of human exploration beyond low earth orbit.

While the project is not fully funded nor vetted at the agency level, much progress has already been made by leveraging and coalescing existing, funded technology work; by forming innovative partnerships; and by a small project team focusing on fast iterative design, test, and execution.

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NASA with partnership from GM, has built R2 which is being called as a “giant leap in robotic technology”.

NASA says Robonaut 2 has been made humanoid in configuration so that it can do what humans can do,  use the same tools as humans, though hopefully it won’t drop them into planetary atmospheres as people occasionally do. And of course it won’t feed on the Oxygen cylinders that humans finish-up fast.

This Droid can easily handle 9Kgs (20lb) weights in Earth gravity, which is pretty good as compared with other dexterous robots.

Robonaut 2, or R2, is a faster, more dexterous and more technologically advanced robot. “Our challenge today is to build machines that can help humans work and explore in space,” said Mike Coats, NASA. “Working side by side with humans, or going where the risks are too great for people, machines like Robonaut will expand our capability for construction and discovery.”

Robonaut 1 was built by NASA in cooperation with Pentagon wildscience division DARPA; the new R2 involved NASA, GM and Oceaneering Space systems.

According to NASA, Robonaut type machines could be especially useful in EVA, extra-vehicular activities, spacewalk. A lot of time and effort is spent kitting an astronaut or cosmonaut up for one of these excursions, which wouldn’t be required with the droid spacewalker. Already, a lot of the work outside the International Space Station and on Shuttle missions is done using the long robotic arms fitted to the spacecraft. For instance, in the case of the ISS, it had a 12-foot-tall “Dextre” robot multitip fitted to the end. Obviously, those things had their limitations which will now have been overcome by use of these Droids.

Watching this Robot in action is the Real thing, watch the video:

As for GM, the car firm hopes that R2′s successors may help get even more humans off its car assembly lines, so cutting down on accidents – and presumably on costs.

“For GM, this is about safer cars and safer plants,” said Alan Taub, GM R&D veep. “When it comes to future vehicles, the advancements in controls, sensors and vision technology can be used to develop advanced vehicle safety systems. The partnership’s vision is to explore advanced robots working together in harmony with people, building better, higher quality vehicles in a safer, more competitive manufacturing environment.”

The idea of using dexterous, human-like robots capable of using their hands to do intricate work is not new to the aerospace industry. The original Robonaut, a humanoid robot designed for space travel, was built by the software, robotics and simulation division at Johnson in a collaborative effort with the DARPA 10 years ago. During the past decade, NASA gained significant expertise in building robotic technologies for space applications. These capabilities will help NASA launch a bold new era of space exploration.

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[Source: Robonaut NASA]

The hand is better known as ProDigits which can be controlled two ways: by myoelectric sensors that register muscle signals from the palm or the remnant finger, or by a pressure sensitive switch from a force resistive sensor. This means that it works out of the box integrating well with your body and muscle signals. The degree of functionality they give back to people is truly incredible.

“Partial-hand amputation represents the largest group of arm amputees, and with ProDigits we finally have a functional state-of-the-art myoelectric prosthesis that we can offer this previously underserved amputee population,” said Jack Uellendahl, C.P.O., clinical prosthetics specialist, Hanger Prosthetics and Orthotics. “With ProDigits, each finger is capable of being a standalone functional unit, allowing for fitting of many different configurations of hand absence. In addition, the movement of the ProDigit prosthesis is natural in appearance, delivering a more elegant solution to partial hand restoration than previously possible.”

You should see the joy it has brought to the patients, watch them share their experience:

The hand has already been tested and used by people across the country. Currently, over 30 people are outfitted with ProDigits, bionic fingers that can actually grab and pick up objects in a way that previous prostheses couldn’t.
Sure the bionic Humanoids World starts, But What’s next? A chip in the Brain?

[via TouchBionics]

Related: DIY: Build a Supercomputer Better than the one your Government has.

To get an idea of how powerful human brain is, Kwabena Boahen, a computer scientist/researcher at Stanford University, conducted some experiments. As per his calculations, he believes that it would require 10 megawatts to power a processor as smart as the human brain. However, his new “Neurogrid” supercomputer is attempting on doing it only at 20 watts. Sounds impossible? Read on.

To give you a better idea, 10 megawatts is the kind of energy a small-medium sized hydroelectric plant produces—20 watts is only enough juice to power up a weak night-lamp. Amazingly, our physical brain runs on this minuscule amount of power, and it’s not very efficient. However, studying this inefficiency could be the key to creating computers that mimic the human brain, the “powerhouse of performance“.

Traditional digital computers depend on millions of transistors opening and closing with near perfection, making an error less than once per 1 trillion times. It is impressive that our computers are so accurate—but that accuracy is a house of cards. A single transistor accidentally flipping can crash a computer or shift a decimal point in your bank account. Engineers ensure that the millions of transistors on a chip behave reliably by slamming them with high voltages—essentially, pumping up the difference between a 1 and a 0 so that random variations in voltage are less likely to make one look like the other. That is a big reason why computers are such power hogs.

On the brains side:

It sounds cockamamy, but it is true. Scientists have found that the brain’s 100 billion neurons are surprisingly unreliable. Their synapses fail to fire 30 percent to 90 percent of the time. Yet somehow the brain works. Some scientists even see neural noise as the key to human creativity. Boahen and a small group of scientists around the world hope to copy the brain’s noisy calculations and spawn a new era of energy-efficient, intelligent computing. Neurogrid is the test to see if this approach can succeed.

Energy efficiency isn’t just a matter of elegance. It fundamentally limits what we can do with computers, Despite the amazing progress in electronics technology—today’s transistors are 1/100,000 the size that they were a half century ago, and computer chips are 10 million times faster—we still have not made meaningful progress on the energy front. And if we do not, we can forget about truly intelligent humanlike machines and all the other dreams of radically more powerful computers.

Most modern supercomputers are the size of a refrigerator and devour $100,000 to $1 million of electricity per year. Boahen’s Neurogrid will fit in a briefcase, run on the equivalent of a few D batteries, and yet, if all goes well, come close to keeping up with these Goliaths.

So far Boahen has managed to fabricate a million neurons onto his new supercomputer. Last year,he managed to get  only 45,000. Looking at the progress, he predicts that  by 2011 he would have 64 million, bringing the project to the equivalent of a mouse’s brain, which will be the biggest achievement we have ever seen in this field.

Reducing the power consumption is the key to upholding Moore’s law.  What we can hope to see is the innovation faster than Moore’s law. This will bring us one step closer to Artificial Intelligence that would make Robotics as good as humans, or perhaps, as flawed as humans.

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[via DiscoverMagazine]

Well, half of the dreams can now come true. Thanks to Japanese robotics venture called Cyberdyne, robot-suit “HAL” (Hybrid Assistive Limb) is now available for rent. Yes, it’s not for sale.

A single leg version rents for $1,570 a month, while a two-leg unit goes for $2,300 a month. Cyberdyne has yet to announce when HAL will go on sale to the public or what the price tag will be.

Too much for being lazy. But a fair deal for the needy.

HAL is a mind-controlled wearable machine that gives humans enhanced mobility.

The HAL exoskeleton helps the wearer to carry out a variety of everyday tasks, including standing up from a chair, walking, climbing up and down stairs, and lifting heavy objects. The suit can operate for almost five hours before it needs recharging.

HAL isn’t quite ready for great grandma just yet. But until it is, Toyota researchers in Japan have built a brain/machine interface (BMI) that has been demonstrated to control a wheelchair using a person’s thoughts. The wheelchair enables a person to make it turn left or right or to move forward simply by thinking the commands –- and it has a 125 millisecond response time.

The suit’s backpack contains a battery and computer controller. When a HAL-assisted person attempts to move, nerve signals are sent from the brain to the muscles, and very weak traces of these signals can be detected on the surface of the skin. The HAL exoskeleton identifies these signals using a sensor, and a signal is sent to the suit’s power unit telling the suit to move in synch with the wearer’s own limbs.

The sample in question was scoetoped from the com Wild-2 in 2004 by the NASA space probe Stardust, which was launched a decade ago in 1999. Having made a close pass to the comet and picked up some of its substance, Stardust then dropped the sample capsule back to Earth in 2006. The main probe, remaining in space, is now to head out again to investigate the comet Tempel-1.

However, “it was possible that the glycine we found originated from handling or manufacture of the Stardust spacecraft itself,” according to NASA’s Dr Jamie Elsila. The scientists have since carried out isotopic analysis of the carbon in the sample, finding that it contains too much carbon-13 to be from Earth.

“We discovered that the Stardust-returned glycine has an extraterrestrial carbon isotope signature, indicating that it originated on the comet,” says Elsila. In his view, this signifies that the basic chemicals from which life can arise may be commonly found beyond the solar system, suggesting that life would be more likely to arise on other worlds.

“The discovery of glycine in a comet supports the idea that the fundamental building blocks of life are prevalent in space, and strengthens the argument that life in the universe may be common rather than rare,” says Dr Carl Pilcher, Director of the NASA Astrobiology Institute.

There’s more from NASA here.

Opportunity, landed successfully at Meri

diani Planum on Mars on January 25, 2004,  three weeks after Spirit. Mission : Completion of the 90-sol mission, discovery of the first meteor on another planet, Heat Shield Rock (Meridiani Planum), and over 2 years studying Victoria crater. The rover narrowly survived dust-storms in 2007, and is now is on it’s way to Endeavour crater.

“Opportunity”, while prowling the haematite steppes of the Meridiani Planum on Mars, has crept up on and photographed a mysterious space boulder or “cobble“.

The interplanetary robot rover expert Astro boffins touts that the object may be alien in origin, rather than from the Mars.

What concerns NASA now is that if this object is confirmed to be of an Alienic origin, more life information about the Aliens can be obtained.

NASA has now released close-up pics of “Block Island” and says that there are plans to confirm its alien extra-Martian origin by use of Opportunity’s alpha-particle X ray spectrometer. Personally, we here on the Reg space desk are hoping it turns out to be a cryptic “nanodiamond” from the mysterious ureilite mother-planetoid, like the pieces discovered in the Nubian desert here on Earth recently.

Meanwhile, Opportunity’s companion rover Spirit remains bogged down in a sand trap in the Gusev crater on the other side of the red planet. NASA brainboxes are engaged in a lengthy series of trials using a test rover in a sandbox on Earth, attempting to figure out a way of getting the trapped droid moving again.

Both Spirit and Opportunity have, however, continued to operate many times longer than they were expected to. NASA engineers originally thought that the Mars-prowling machines might manage to travel as much as a kilometer from their landing sites over lifetimes measured in months. In fact both machines remain in operation well over 5 years from landing. Opportunity has moved more than 17km as of the last update, and Spirit almost 8km.

In order to take the research further, NASA now plans to despatch a new, much larger – Humvee sized – nuclear powered rover (called the Mars Science Laboratory or MSL) to Mars in 2011, following development and funding problems. The MSL had originally been planned to launch later this year, but due to higher expectations from the project, it had been delayed.

We’ve seen Mosquito sized robots in Sci-fi movies that can go into Human body to provide inner insights and fix problems or introduce a new one (like in matrix). Alternatively, they act as a surveillence device.

Well, it’s not far from reality, thanks to ITU (Israel’s Technion University), they have unveiled a tiny robot, made using Micro-Electro-Mechanical Systems (MEMS) technology. It’s capable of crawling through a human’s veins to provide diagnosis and potentially treat artery blockage and cancer.

This Tiny Robot ( almost 1mm in diameter) is very different from the others we have seen so far. This is powered by a unique source of energy, your body, and external Magnetic fields. It has neither engine nor onboard controls, instead some very Techie coils that allows it to be propelled forward by a magnetic field wielded on it from outside the patient’s body.

Controlling the tiny bot externally means that scientist have been able to shrink it to a previously impossibly tiny scale, allowing it to crawl its way through the typical human body’s veins and arteries using miniscule outstretched arms which grip the vessel walls. Too good to be believeable.

So What about difficulties in Movement?

Scientists bet that the mini bot can even withstand massive blood flow and is able to push forward regardless of the magnetic field actuation direction, doing away with any need for exact localisation and direction retrieval.

The inbuilt controller can move the little crawly creature in increments, with its speed of up to nine millimeters a second regulated by varying external magnetic field frequencies. Outside control also means the robot can be made to work for an unlimited amount of time, rather than suddenly – not to mention inconveniently – keeling over to die of battery failure in the middle of a medical procedure.

The team at ITU quotes:

A small cross sectional area on the tiny robot apparently allows fluids to flow with minimal interference making intra-vascular motion more feasible, and opening up the possibility of minimally invasive medical treatments, as well as diagnosis within the body. Researchers are also apparently toying with the idea of attaching miniscule cameras to the bot, as well as other “tools” it may need to perform internal surgery.

What’s Next? Technion researchers say they’re also looking at putting the ant-like robot to work in urban water distribution systems, to look for any leaks that need plugging. This could be like ants will monitor the current location with a reflective light of these swimming ants in water, if they move out of a specified co-ordinates of the path, there is a potential leak.

The researchers have work-in-progress to commercialize them.

We all are fascinated by Robotics. IT can be surprising at moments when people come up with amazing things. sometimes it they are pathetically dumb. Luckily this one is NOT! “Do Robotics” has rolled its latest software-ready autonomous robot off the production line at its Colorado home base. Like its first two robotic offerings, RoBe:Do’s third robot, aptly named “Three”, comes fully assembled and ready and waiting for you to add the netbook of your choice to act as the robot’s brain.

Three is RoBe:Do’s greenest robot to date thanks to a simplified design that results in less aluminum, electronics and rechargeable batteries. A three-sensor digital infrared navigation array option also minimizes required electronics, while detecting objects within 10-inches.

The netbook “brain” sits atop a sturdy aluminum mount and connects to the robot via USB. If bigger brains are your thing then you might want to opt for the optional larger robot chassis, which can accommodate 6+ pound laptops. The chassis sits atop two 6.7” tires powered by 2 x 120 RPM gearhead motors, with a third, smaller multi-directional rear wheel adding support.

All of RoBe:Do’s robots can be controlled with a Linux, Mac or Windows PC using various software languages and tools such as C, C++, C#, Flash AS3, Java, .NET, Python, VBScript and Visual Basic to name a few. Three comes with attachment mechanisms to facilitate the addition of USB plug-and-play sensors, I/O controllers, actuators or cases to expand the capabilities of the robot.

This means making and delivering popcorn is just the tip of the iceberg for Three. If nothing else it could act as your personal netbook caddy.

RoBe:Do’s Three stands 6.5-inches tall, measures 12-inches long and 12-inches wide and tips the scales at 4 pounds. It is custom built and is available now from the regular price of USD$439.