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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.

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.

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:

Researchers at Purdue University have developed two new techniques for computer-vision technology that mimic how humans perceive three-dimensional shapes.The techniques, heat mapping and heat distribution, apply mathematical methods to enable machines to perceive three-dimensional objects by mimicking how humans perceive three-dimensional shapes by instantly recognizing objects no matter how they are twisted or bent, an advance that could help machines see more like people.

A new development in virtual cameras at the University of Abertay Dundee is developing the pioneering work of James Cameron’s blockbuster Avatar using a Nintendo Wii-like motion controller – all for less than £100.Avatar, the highest-grossing film of all time, used several completely new filming techniques to bring to life its ultra-realistic 3D action. Now computer games researchers have found a way of taking those techniques further using home computers and motion controllers.James Cameron invented a new way of filming called Simul-cam, where the image recorded is processed in real-time before it reaches the director’s monitor screen. This allows actors in motion-capture suits to be instantly seen as the blue Na’vi characters, without days spent creating computer-generated images.

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.

Microsoft Research who brought us some wonderful technologies such as the incredible Photosynth continue to impress with a much improved web mapping application integrated with the company's new Bing search engine. During the TED 2010 conference, Microsoft engineer Blaise Aguera y Arcas demoed the new Bing augmented reality maps showing real-time registration of video taken with a smart phone and street-view type maps. He showed how the live video can be overlayed over the static images and additional information about the area can be accessed via a Web interface. Much of this is made possible because of the advanced computer vision technology that has been developed in the past decade at Microsoft Research. The Seadragon technology is the back-end that makes it possible to manipulate such vast amounts of data in real-time. Microsoft has also integrated Photosynth and Worldwide telescope into their maps product. You are probably wondering what does this have to do with robotics other than the fact that it is a very impressive application? I can imagine robots using Bing maps to keep localized within a city. One of the most difficult and important problem in robotics is that of Simultaneous Localization and Mapping. Bing maps solve the mapping problem and the new vision techniques (with a bit of help from GPS) can be used to solve the localization problem. The registered video can be used by a robot to localized itself when it goes out to buy your weekly groceries.  You can watch the 10-minute demo below; I bet that it won't be long before Microsoft makes these new features available to us all for free.

PC-compatible industrial computers are increasing in computing power at a rapid rate due to the availability of multi-core microprocessor chips, and Microsoft Windows has become the de-facto software platform for implementing human-machine interfaces (HMIs). PCs are also becoming more reliable. With these trends, the practice of building robotic systems as complex multi-architecture, multi-platform systems is being challenged. It is now becoming possible to integrate all the functions of machine control and HMI into a single platform, without sacrificing performance and reliability of processing. Through new developments in software, we are seeing industrial systems evolving to better integrate Windows with real-time functionality such as machine vision and motion control. Software support to simplify motion control algorithm implementation already exists for the Intel processor architecture.

You might think that some devices in the modern age have reached their maximum development level, such as the common desk-lamp, but you would be wrong. Natan Linder, a student from The Massachusetts Institute of Technology (MIT) has created a robotic version that can not only light your room, but project internet pages on your desk as well. It is an upgrade on the AUR lamp from 2007, which tracks movements around a desk or table and can alter the color, focus, and strength of its light to suit the user’s needs. The LuminAR comes with those abilities, and much more. The robotic arm can move about on its own, and combines a vision system with a pico projector, wireless computer and camera. When turned on, the projector will look for a flat space around your room on which to display images. Since it can project more than one internet window, you can check your email and browse another website at the same time.

The latest episode of the Robots Podcast looks at the following scenario: Imagine being able to throw a hand-full of smart matter in a tank full of liquid and then pulling out a ready-to-use wrench once the matter has assembled. This is the vision of this episode's guests Michael Tolley and Jonas Neubert from the Computational Synthesis Laboratory run by Hod Lipson at Cornell University, NY. Tolley and Neubert give an introduction into Programmable Matter and then present their research on stochastic assembly of matter in fluid, including both simulation (see video above) and real-world implementation. Read on or tune in!

The vision of a smarter grid is of course a lovely thing to behold: an electric power system that’s much more interactive, interoperable, reliable, and robust—“self-healing,” even. That’s why so much excitement attended the news this time last year that the U.S. stimulus bill would contain billions of dollars in new funding to support smart grid construction, and the news six months later than the National Institute for Standards and Technology was issuing draft standards and a roadmap for completing standardization of the smart grid (the Framework and Roadmap for Smart Grid Interoperability Standards, issued in final form in January). And it's the reason too why such high expectations ride on the avalanche of smart meter installation projects launched in the last year.

Taylor Veltrop used a Kinect to read his arm movements which were then carried out by a robot. The robot was programmed using Willow Garage's open-source robot operating system (ROS). As Kit Eaton suggest, this quick experiment provides an illustration of the path towards robotic avatars.

In this project we want to analyze and test the idea of incorporating a network of robots (robots, intelligent sensors, devices and communications) in order to improve life quality in urban areas. The URUS project is focused in designing a network of robots that in a cooperative way interact with human beings and the environment for tasks of assistance, transportation of goods, and surveillance in urban areas. Specifically, our objective is to design and develop a cognitive network robot architecture that integrates cooperating urban robots, intelligent sensors, intelligent devices and communications.

In recent years, ‘social’ robots—cleaning robots, nursing-care robots, robot pets and the like—have started to penetrate into people’s everyday lives. Saerbeck and other robotics researchers are now scrambling to develop more sophisticated robotic capabilities that can reduce the ‘strangeness’ of robot interaction. “When robots come to live in a human space, we need to take care of many more things than for manufacturing robots installed on the factory floor,” says Haizhou Li, head of the Human Language Technology Department at the A*STAR Institute for Infocomm Research. “Everything from design to the cognitive process needs to be considered.”

Researchers at MIT's Object Based Media Group (OBMG), led by professor Michael Bove, have developed a 3D hologram using the Xbox Kinect and a laptop. Three GPUs on a graphic card are used to generate diffraction patterns that produce a Star-Wars-Style hologram at 15 frames per second. More information is available in a PopSci web article.