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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.

This is a site for all things about amateur Unmanned Aerial Vehicles (UAVs). Use the tabs and drop-down menus above to navigate the site. These are our Arduino-based open source autopilot projects: * ArduPilot, a low-cost autopilot system for planes. * ArduCopter, a fully-autonomous quadcopter system (heli autopilot coming soon). * BlimpDuino, an autonomous blimp with both infrared and ultrasonic guidance.

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.)

Bipedal humanoid robots can step over obstacles and negotiate stairs where their wheeled counterparts cannot, but this comes with the risk of falling down.  Naturally, humanoid robots will never be accepted in society if they break when they fall down.  The bigger the robot, the more likely it is that it will damage itself during a fall and be unable to get up. In 2003 the HRP-2P was the first full-scale humanoid that could fall over safely and get back up, and so far remains alone; not even Honda’s ASIMO can do this.  As soon as it detected that it was falling, the HRP-2P would bend its knees and back, which helped to reduce the ground impact.  This motion, called “UKEMI”, is quite similar to how the SONY QRIO would react when falling over to reduce the risk of damaging its components.

Cooking is an art sometimes forgotten in the robotics world, but James, the PR2 robot, and Rosie, another robot from CoTeSys (Cognition for Technical Systems) in Munich have joined forces to show that robots can be of great use in the kitchen as well. They made some pretty successful-looking pancakes and used various tools around the Assisted Kitchen to show off their skills. The main chef in the experiment was Rosie, who used her broad arms and high levels of dexterity to flip and cook the pancakes. As you can see in the video, she is a bit on the slow side, but she’s also extra careful and gets it done right. She is capable of adjusting the way she pours the batter based on the weight of the bowl, demonstrating some impressive planning and a good use of her sensors, which allow the bot to recognize how much batter she has already poured.

Continuing to work on a humanoid helper robot called ARMAR, the Collaborative Research Center 588: Humanoid Robots at the University of Karlsruhe began planning ARMAR-IIIa (blue) in 2006. It has 43 degrees of freedom (torso x3, 2 arms x7, 2 hands x8, head x7) and is equipped with position, velocity, and force sensors.  The upper-body has a modular design based on the average dimensions of a person, with 14 tactile sensors per hand.  Like the previous versions, it moves on a mobile platform.  In 2008 they built a slightly upgraded version of the robot called ARMAR-IIIb (red).  Both robots use the Karlsruhe Humanoid Head, which has 2 cameras per eye (for near and far vision).  The head has a total of 7 degrees of freedom (neck x4, eyes x3), 6 microphones, and a 6D inertial sensor.

In a recent video, Willow Garage researcher Eitan Marder-Eppstein describes the open-source navigation stack they've released as version 1.0. The code, available at http://ros.org/wiki/navigation, was designed to be flexible and cross-platform, he says, and could be used in anything from a small iRobot Create-based bot to a large multi-sensor robot like Willow's own PR2 (which Spectrum has covered in detail here and here).

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:

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.

Rosie, the robot who kept house for the title family in "The Jetsons," a 1960s animated television show, has at last come alive—sort of. Before you'll see a robot slicing cucumbers in your kitchen, researchers will need to make these mechanical servants smarter. Here's how three teams are tackling this challenge.

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.

ALSOK, a security firm that specializes in robot guards, has sent their drones into shopping malls, office buildings, and museums.  This video shows one of them patrolling an art gallery.  Not surprisingly, even in Japan, the sight of a robot patrolling its beat is more than enough to distract some of the visitors from the actual works of art!

NAMO (Novel Articulated MObile platform)  is a humanoid robot built by The Institute of Field Robotics (FIBO) at King Mongkut’s University of Technology Thonburi in Thailand. FIBO is active in the RoboCup scene and have developed a wide range of robot types, including an experimental biped.  NAMO was unveiled on March 29th 2010, serving as FIBO’s mascot as part of the university’s 50 year anniversary celebrations.  NAMO will be used to welcome people to the university and may be deployed at museums.  Given its friendly appearance and functionality, it could be used to research human robot interaction and communication. NAMO is 130cm (4′3″) tall and has 16 degrees of freedom.  It moves on a stable three-wheeled omnidirectional base, and is equipped with a Blackfin camera for its vision system.  It is capable of simple gesture recognition, visually tracks humans or objects of interest automatically, and can speak a few phrases in a child-like voice (in Thai).

GetRobo has pointed out a new website by Francisco Paz, which focuses on his experience building an open source personal robot called Qbo.  From the few images on the site Qbo looks remarkably well made and quite similar to NEC’s PaPeRo, meaning it might be used to experiment with image processing, speech recognition, speech synthesis, and (assuming it has wheels) obstacle detection and SLAM.  He also mentions in his blog some of the open source software that’s out in the wild such as OpenCV, Festival, and Sphinx, which would allow you to do some of that.

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.

Remember A-pod, the realistic ant-like hexapod from last year?  Well its creator Kare Halvorsen has uploaded a brand new video showcasing its improved capabilities, and it’s a stunner.  His last video, posted around this time last year, went viral due to the robot’s realistic movements. This year, he ups the ante by showing it walking around and manipulating objects. Some of his past robot projects can be seen in brief snippets, and they’re not too shabby either.  Imagine a horde of these guys with sophisticated A.I.!

Dennis Hong, a professor of mechanical engineering and director of Virginia Tech's Robotics & Mechanisms Laboratory, or RoMeLa, has created robots with the most unusual shapes and sizes -- from strange multi-legged robots to amoeba-like robots with no legs at all. Now he's unveiling a new robot with a more conventional shape: a full-sized humanoid robot called CHARLI, or Cognitive Humanoid Autonomous Robot with Learning Intelligence. The robot is 5-foot tall (1.52 meter), untethered and autonomous, capable of walking and gesturing. But its biggest innovation is that it does not use rotational joints. Most humanoid robots -- Asimo, Hubo, Mahru -- use DC motors to rotate various joints (typically at the waist, hips, knees, and ankles). The approach makes sense and, in fact, today's humanoids can walk, run, and climb stairs. However, this approach doesn't correspond to how our own bodies work, with our muscles contracting and relaxing to rotate our various joints.

One solution to getting robots to perform complex and/or variable tasks is to teleoperate them. Arguably this removes a significant portion of having a robot in the first place, but there will inevitably be tasks that even the most complex and well programmed robot just won’t be prepared for. If you’ve been reading BotJunkie for the past three years, you may remember Monty, a telepresence humanoid from Anybots. Monty was a bit difficult to control, and at the very least required some training.