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Remember Hitachi’s little helper robot, EMIEW 2 (Excellent Mobility and Interactive Existence as Work-mate)?  It’s been a couple of years since we heard anything regarding the project and we feared the worst.  Hitachi has put those fears to rest by holding a news conference to show off its new enhanced voice recognition and driving performance! Known primarily for its unique legs which have wheels for feet, EMIEW 2 can drive at up to 6km/h to keep pace with people.  If it needs to carry something it can kneel down (for added stability) and scoot around, and thanks to its bipedal legs it can step over obstacles that are too high to drive over.  Now it has been given adaptive suspension control technology which increases its stability when driving over bumpy terrain such as elevator doors.  During the press demonstration, EMIEW 2′s springy legs bobbed independently as it drove over cables and uneven flooring.

Justin is a dexterous humanoid robot that can make coffee. Now it's learning to fix satellites. Justin was developed at the Institute of Robotics and Mechatronics, part of the German Aerospace Center (DLR), in Wessling, Germany. The robot has different configurations, including one with wheels. The space version has a head, torso, and arms, but no wheels or legs, because it will be mounted on a spacecraft or satellite. The goal is to use Justin to repair or refuel satellites that need to be serviced. Its creators say that ideally the robot would work autonomously. To replace a module or refuel, for example, you'd just press a button and the robot would do the rest. But that's a long-term goal. For now, the researchers are relying on another approach: robotic telepresence. A human operator controls the robot from Earth, using a head-mounted display and a kind of arm exoskeleton. That way the operator can see what the robot sees and also feel the forces the robot is experiencing.

California-based company Anybots continues work on a telepresence robot that can take communication to a whole new level by eliminating the need for people to actually be present at board meetings or conferences. Because God knows executives work hard enough. The idea behind QA, the robot, is to interact with people, such as clients or partners, from anywhere in the world, which will save a lot of money on travel costs and different remote-communications equipment. Designed not unlike a sophisticated Skype program, QA relies on a Wi-Fi connection to allow users to interact through video, sound and diagrams projected from and onto the robot’s interface. With a sleek white exterior design, the armless 5-foot robot looks just about how you would expect a robot tailored for the boardroom to look. His rectangular-shaped face with two big eyes reminds a bit of Steven Spielberg’s E.T., so people should warm up to it fairly quickly.

Scientists at the Johns Hopkins University Applied Physics Laboratory (APL) were awarded no less than $34.5 million by the Defense Advanced Research Projects Agency (DARPA) to continue their outstanding work in the field of prosthetic limb testing, which has seen them come up with the most advanced model yet. Their Modular Prosthetic Limb (MPL) system is just about ready to be tested on human subjects, as it has proved successful with monkeys. Basically, the prosthetic arm is controlled by the brain through micro-arrays that are implanted (gently) in the head. They record brain signals and send the commands to the computer software that controls the arm. To be honest, it will be interesting to see just how these hair-chips are attached to the brain, but the APL say clinical tests have shown the devices to be entirely harmless. The monkeys didn’t mind them too much, at least.

The purpose of this essay is to examine whether or not there would be practical reasons for creating a conscious, emotional machine.  I will not delve to deeply into whether or not it is possible to create such a machine, as the argument as to what exactly would constitute a living conscious machine seems largely unsettled.  Rather I will concentrate on whether or not we should create such a machine, if the possibility becomes available to us.  Are there uses for such a machine that could not be satisfied by a complex automaton?  Is there anything about real emotional response that would be necessary for a machine to operate autonomously, and still interact with human beings?  What are the dangers? What are the ethical ramifications? It is questions such as these that will be the interest of this paper.

We are entering the robotic age. All over the world, we see research projects and companies working on realistic, market driven robots, with impressive realizations ranging from intelligent vacuum cleaners to humanoid robots.   This is a very exciting time and some people see in the current situation many common points with the early days of the computer industry. However, like PCs in the early 80's, today's robots are still incompatible in term of software. There is yet no standard way to reuse one component from one robot to the other, which is needed to have a real software industry bootstraping. And most attempts have been failing to provide tools genuinely adapted to the complex need of robot programming.   Here at Gostai, we believe that the industry needs a powerful robotics software platform, ready to face the challenges of Artificial Intelligence and autonomous robots programming.

Researchers at the University of Pennsylvania are developing algorithms to enable robots to learn to read like a human toddler. Using a Willow Garage PR2 robot (nicknamed Graspy), the researchers demonstrate the ability for a robot to learn to read anything from simple signs to full-length warnings. Graspy recognizes the shapes of letters and associates them with sounds. Part of the computer vision challenge is reading hundreds of different fonts. More information is available in a Psyorg article and from the ROS website.

This is Treebot. As you might expect, Treebot was designed to do one thing: climb trees. It is by no means the first robot able to do this, but its arboreal predecessors (RiSE and Modsnake and accidentally PackBot are just a few) weren't autonomous and didn't have the skills necessary to negotiate the complex network of branches that you tend to find on trees worth climbing.

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.

EARL (that would be, Enhanced Automated Robotic Launcher) is a second generation bowling robot. Let me explain to you why a bowling robot is necessary at all: apparently, EARL is “invaluable in the many studies necessary to keep up with the ever-changing bowling ball industry… [EARL is] the future of bowling research.” Hmm. That’s worth pondering for a minute or two. Well, I won’t pretend to understand it, but that doesn’t mean I’m not impressed with the fact that EARL can throw bowling balls at 24 MPH and spin them up at 900 RPM, much faster than a human is capable of, which I guess is why people seemed to assume that the robot would win… Does it say something about the state of robotics, or something about the sport? Either way, bowling seems like a game with an extremely limited amount of random variables, and sooner or later (probably sooner) the only thing worthy of a news story will be a robot arm not bowling a perfect 300.

The Russian policeman waved at the orange van zigzagging around the empty plaza, ordering it to stop. The van didn’t, so the officer stepped closer to address the driver. But there was no driver. The van is an autonomous vehicle developed at the University of Parma’s Artificial Vision and Intelligent Systems Laboratory, known as VisLab. Crammed with computers, cameras, and sensors, the vehicle is capable of detecting cars, lanes, and obstacles -- and drive itself. The VisLab researchers, after getting tired of testing their vehicles in laboratory conditions, decided to set out on a real-world test drive: a 13,000-kilometer, three-month intercontinental journey from Parma to Shanghai. The group is now about halfway through their trip, which started in July and will end in late October, at the 2010 World Expo in China. (See real time location and live video.)

Walking, swallowing, respiration and many other key functions in humans and other animals are controlled by Central Pattern Generators (CPGs). In essence, CPGs are small, autonomous neural networks that produce rhythmic outputs, usually found in animal's spinal cords rather than their brains. Their relative simplicity and obvious success in biological systems has led to some success in using CPGs in robotics. However, current systems are restricted to very simple CPGs (e.g., restricted to a single walking gait). A recent breakthrough at the BCCN at the University of Göttingen, Germany has now allowed to achieve 11 basic behavioral patterns (various gaits, orienting, taxis, self-protection) from a single CPG, closing in on the 10–20 different basic behavioral patterns found in a typical cockroach. The trick: Work with a chaotic, rather than a stable periodic CPG regime. For more on CPGs, listen to the latest episode of the Robots podcast on Chaos Control, which interviews Poramate Manoonpong, one of the lead researchers in Göttingen, and Alex Pitti from the University of Tokyo who uses chaos controllers that can synchronize to the dynamics of the body they are controlling.

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.”