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Can a team of soccer-playing robots beat the human World Cup champions by 2050? That's the ultimate goal of RoboCup, an international tournament where teams of soccer robots compete in various categories, from small wheeled boxes to adult-size humanoids. IEEE Spectrum's Harry Goldstein traveled to Singapore to attend RoboCup 2010 -- and check out how the man vs. machine future of soccer is playing out.

Carnegie Mellon has taught its robotic snake to climb trees, though one hopes it won’t start offering your spouse apples. “Uncle Sam” (presumably named for its red, white, and blue markings) is a snake robot built from modular pieces. The latest in a line of ‘modsnakes’ from Carnegie Mellon’s Biorobotics Lab, Uncle Sam can move in a variety of different ways including rolling, wiggling, and side-winding. It can also wrap itself around a pole and climb vertically, which comes in handy when scaling a tree. You have to watch this thing in action. There is something incredibly life-like, and eerie, about the way it scales the tree outdoors and then looks around with its camera ‘eye’. Projects like Uncle Sam show how life-mimicking machines could revolutionize robotics in the near future.

An innovatice camera system could in future enhance security in public areas and buildings. Smart Eyes works just like the human eye. The system analyzes the recorded data in real time and then immediately flags up salient features and unusual scenes.  »Goal, goal, goal!« fans in the stadium are absolutely ecstatic, the uproar is enormous. So it‘s hardly surprising that the security personnel fail to spot a brawl going on between a few spectators. Separating jubilant fans from scuffling hooligans is virtually impossible in such a situation. Special surveillance cameras that immediately spot anything untoward and identify anything out of the ordinary could provide a solution. Researchers from the Fraunhofer Institute for Applied Information Technology FIT in Sankt Augustin have now developed such a device as part of the EU project »SEARISE – Smart Eyes: Attending and Recognizing Instances of Salient Events«. The automatic camera system is designed to replicate human-like capabilities in identifying and processing moving images.

UC3M's ASIROV Robotic Satellite Chaser Prototype ASIROV, the Acoplamiento y Agarre de Satélites mediante Sistemas Robóticos basado en Visión (Docking and Capture of Satellites through computer vision) would use computer vision tech to autonomously chase down satellites in orbit for repair or removal. Image courtesy of Universidad Carlos III de Madrid Spanish robotics engineers have devised a new weapon in the battle against zombie-sats and space junk: an automated robotics system that employs computer vision technology and algorithmic wizardry to allow unmanned space vehicles to autonomously chase down, capture, and even repair satellites in orbit. Scientists at the Universidad Carlos III de Madrid (UC3M) created the system to allow for the removal of rogue satellites from low earth orbit or the maintenance of satellites that are nearing the ends of their lives, prolonging their service (and extending the value of large investments in satellite tech). Through a complex set of algorithms, space vehicles known as “chasers” could be placed into orbit with the mission of policing LEO, chasing down satellites that are damaged or have gone “zombie” and dealing with them appropriately.

Researchers at CMU and Intel are attempting to map and understand human brain activity well enough that individual words can be detected. Currently, giant MRI machines are being used but the future holds smaller devices that can be worn like a helmet according to Dean Pomerleau, senior researcher at Intel. The efficiency and productivity of word detection will be superior to existing technology that allows an operator to simply control a cursor. This technology will no doubt make its way into robotic telepresence applications including remote surgery and construction in dangerous environments such as the ocean and space.

Scientists have great expectations that nanotechnologies will bring them closer to the goal of creating computer systems that can simulate and emulate the brain's abilities for sensation, perception, action, interaction and cognition while rivaling its low power consumption and compact size. DARPA for instance, the U.S. military's research outfit known for projects that are pushing the envelope on what is technologically possible, has a program called SyNAPSE that is trying to develop electronic neuromorphic machine technology that scales to biological levels. Started in late 2008 and funded with $4.9 million, the goal of the initial phase of the SyNAPSE project is to "develop nanometer scale electronic synaptic components capable of adapting the connection strength between two neurons in a manner analogous to that seen in biological systems, as well as, simulate the utility of these synaptic components in core microcircuits that support the overall system architecture."

A major hurdle in the ambitious quest to design and construct a radically new kind of quantum computer has been finding a way to manipulate the single electrons that very likely will constitute the new machines' processing components or "qubits."

Andrew Phillips holds the title of Scientist with Microsoft Research Cambridge, and he's working on a method of programming that compiles into DNA. Part of this involves a visual programming language called Stochastic Pi Machine, or SPiM. This system models biological processes to help give researchers feedback on how organisms will react to modifications. The hope is that this can be used to help scientists program for large biological systems using modular components compiled to DNA. Yes, I’m in way over my head here, but I do my best to ask Andrew about the role this will play in medical treatment going forward, what it means to DNA computing, and the ability of back-engineering the genetic code we don’t use now

Willow Garage is organizing a workshop at the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR) 2010 in San Francisco to discuss the intersection of computer vision with human-robot interaction. Willow Garage is the hardware and open source software organization behind the Robot Operating System (ROS) and the PR robot development platform. Here’s a recent video from Willow Garage of work done at the University of Illinois on how robots can be taught to perceive images:

Andrew Phillips holds the title of Scientist with Microsoft Research Cambridge, and he's working on a method of programming that compiles into DNA. Part of this involves a visual programming language called Stochastic Pi Machine, or SPiM. This system models biological processes to help give researchers feedback on how organisms will react to modifications. The hope is that this can be used to help scientists program for large biological systems using modular components compiled to DNA. Yes, I’m in way over my head here, but I do my best to ask Andrew about the role this will play in medical treatment going forward, what it means to DNA computing, and the ability of back-engineering the genetic code we don’t use now.

The other day I was critical of the UK’s nanotechnology strategy document. However, I am a great admirer of the UK scientists and engineers working in the field of nanotechnology, which makes the recent strategy document such a double disappointment. To sort of atone for my criticism, I wanted to highlight a UK-based researcher, Professor Philip Moriarty at the University of Nottingham, who first came to my attention a few years back on the pages of Richard Jones’ blog Soft Machines , when Moriarty had organized a debate on the subject of radical nanotechnology, otherwise known as molecular nanotechnology. I also recently noted his ability to secure funding for his research to test the theories of molecular manufacturing, and wondered if he can do it why aren’t more molecular manufacturing theorists doing it.

The VMKit project is an implementation of a JVM and CLI virtual machine (.Net is an implementation of the CLI). It translates Java bytecode and MSIL in the LLVM IR and uses the LLVM framework for optimizations and compilation. For garbage collection, it uses MMTk. You can get and build the source today.

The animal world has been a source of inspiration for many robotic designs as of late, as who better to ask about life-like movements than mother Nature herself? Up until now, though, these designs had been mostly focused on small critters, like cockroaches, and simulating properties such as adaptability and speed. But what happens when we start looking at bigger and stronger animals? Like, say, an elephant? Well, Festo’s Bionic Handling Assistant is what happens. This innovation might seem like just another robotic arm at first glance, but the video demonstrates quite vividly how this design is such a big improvement over previous versions. Modeled after the elephant’s mighty trunk, this arm possesses great dexterity, flexibility and strength; operating with smooth, yet firm motions, and can pick up and move any kind of object from one place to another. It’s FinGripper fingers give it “an unparalleled mass/payload ratio”, and it has no problem twisting, assembling and disassembling things, such as the experimental toy in the video.

Tigal announced the VoiceGP family of products under its VeeaR brand of voice and speech recognition products. The product family consists of the VoiceGP module and two development kits with bundled development software. It combines all the hardware and software required for easy and cost effective development and implementation of speech synthesis and multi-language speaker independent and speaker dependent speech recognition capabilities to virtually any application, says the manufacturer. The VoiceGP Module is based on Sensory's RSC-4128 mixed signal processor. Its 42x72mm footprint and two 28-pin connectors with 2.54mm pin spacing make the module breadboard friendly and suitable for prototype boards.

In the 1970s the CIA had developed a miniature listening device that needed a delivery system, so the agency’s scientists looked at building a bumblebee to carry it. They found, however, that the bumblebee was erratic in flight, so the idea was scrapped. An amateur entymologist on the project then suggested a dragonfly and a prototype was built that became the first flight of an insect-sized machine. A laser beam steered the dragonfly and a watchmaker on the project crafted a miniature oscillating engine so the wings beat, and the fuel bladder carried liquid propellant. Despite such ingenuity, the project team lost control over the dragonfly in even a gentle wind. “You watch them in nature, they’ll catch a breeze and ride with it. We, of course, needed it to fly to a target. So they were never deployed operationally, but this is a one-of-a-kind piece.”

Until now you can have big elaborate robots or very small microbots but it is very difficult to have both. A blog post from New Scientist (where this video is from) points out the research on microbots, very small machines that will move, navigate and perform simple tasks. The ability to remotely power a microbot, thus eliminating the need for onboard battery or fuel, is already proven and one of the methods is the application of an AC field to a liquid where the robot is located. This microbot is essentially a diode, a one-way electric conductor. The different electric charges at its ends force the neighboring ions to move thus creating a small thrust that propels the bot. The team of Rachita Sharma and Orlin Velev from North Carolina State University developed a method where a controlled application of an additional DC field changes the ion distribution around the microbot and this time the ion field creates a torque that rotates the microbot. The DC field is applied until the completion of a 180-degree turn. Then the microbot moves again, now in the opposite direction. It is only 1.3mm long and as claimed by other scientists like Vesselin Paunov from the University of Hull, UK this arrangement can be further scaled down where it can be useful for diagnostic and localized drug supply applications.

Robots might one day trace the origin of their consciousness to recent experiments aimed at instilling them with the ability to reflect on their own thinking. Although granting machines self-awareness might seem more like the stuff of science fiction than science, there are solid practical reasons for doing so, explains roboticist Hod Lipson at Cornell University's Computational Synthesis Laboratory.

So after all that you are probably asking, “What is SimpleCV?” It is an open source computer vision framework that lowers the barriers to entry for people to learn, develop, and use it across the globe. Currently there are a few open source vision system libraries in existence, but the downside to these is you have to be quite the domain expert and knowledgeable with vision systems as well as know cryptic programming languages like C. Where SimpleCV is different, is it is “simple”. It has been designed with a web browser interface, which is familiar to Internet users everywhere. It will talk to your webcam (which most computers and smart phones have built in) automatically. It works cross platform (Windows, Mac, Linux, etc). It uses the programming language Python rather than C to greatly lower the learning curve of the software. It sacrifices some complexity for simplicity, which is needed for mass adoption of any type of new technology.