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.

Robot motion planning has traditionally been used to avoid collisions when moving a robot arm. Avoiding collisions is important, but many other desirable criteria are often ignored. For example, motions that minimize energy will let the robot extend its battery life. Smoother trajectories may cause less wear on motors and can be more aesthetically appealing. There may be even more useful criteria, like keeping a glass of water upright when moving it around. This summer, Mrinal Kalakrishnan from the Computational Learning and Motor Control Lab at USC worked on a new motion planner called STOMP, which stands for "Stochastic Trajectory Optimization for Motion Planning". This planner can plan paths for high-dimensional robotic systems that are collision-free, smooth, and can simultaneously satisfy task constraints, minimize energy consumption, or optimize other arbitrary criteria. STOMP is derived from gradient-free optimization and path integral reinforcement learning techniques (Policy Improvement with Path Integrals, Theodorou et al, 2010).

Japan’s National Institute of Advanced Industrial Science and Technology (AIST) has detailed the software used to make their robot dance (see some nice photos over at Pink Tentacle) in a recent press release.  The software, dubbed Choreonoid (Choreography and Humanoid), is similar to conventional computer animation software.  Users create key poses and the software automatically interpolates the motion between them.  What makes the software unique is that it also corrects the poses if they are mechanically unstable, such as modifying the position of the feet and waist, allowing anyone to create motions compatible with the ZMP balancing method.  This is especially important for robots like the HRP-4C, where complicated motions could easily cause it to fall over.

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.

Japanese robotics company HiBot has unveiled a nimble snake bot capable of moving inside air ducts and other narrow places where people can't, or don't want to, go. The ACM-R4H robot, designed for remote inspection and surveillance in confined environments, uses small wheels to move but it can slither and undulate and even raise its head like a cobra. The new robot, which is half a meter long and weighs in at 4.5 kilograms, carries a camera and LEDs on its head for image acquisition and can be fitted with other end-effectors such as mechanical grippers or thermo/infrared vision systems. Despite its seemingly complex motion capabilities, "the control of the robot is quite simple and doesn't require too much training," says robotics engineer and HiBot cofounder Michele Guarnieri.

Although signal processing is usually associated with digital signal processors, it is becoming increasingly evident that FPGAs are taking over as the platform of choice in the implementation of high-performance, high-precision signal processing. For many such applications, the choice generally boils down to using either a single FPGA, a FPGA with an associated DSP processor or a farm of DSP processors.

CHELMSFORD, MA.  October 7, 2010  Mercury Computer Systems, Inc. (NASDAQ: MRCY, www.mc.com), a trusted ISR subsystems provider, announced the availability of OpenSAL, an open source version of its award-winning Scientific Algorithm Library (SAL) for vector math acceleration. SAL is a high-throughput, low-latency signal processing library containing efficient algorithms with the fewest possible instructions and computing resources. OpenSAL provides a robust API, C code reference design and documentation for over 400 SAL math functions.

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.

When I first heard about compressed sensing, I was skeptical. There were claims that it reduced the amount of data required to represent signals and images by huge factors and then restored the originals exactly. I knew from the Nyquist-Shannon sampling theorem that this is impossible. But after learning more about compressed sensing, I’ve come to realize that, under the right conditions, both the claims and the theorem are true. The Nyquist-Shannon sampling theorem states that to restore a signal exactly and uniquely, you need to have sampled with at least twice its frequency. Of course, this theorem is still valid; if you skip one byte in a signal or image of white noise, you can’t restore the original. But most interesting signals and images are not white noise. When represented in terms of appropriate basis functions, such as trig functions or wavelets, many signals have relatively few non-zero coefficients. In compressed (or compressive) sensing terminology, they are sparse.

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.

We had to cover monads eventually, and there are many great monad tutorials out there (see, for example, here: http://www.haskell.org/haskellwiki/Tutorials#Using_monads). In fact, there are web resources concerned solely with organizing the many monad tutorials available in the wild, and developing new monad tutorials seems to be a popular sport in the Haskell community.Today, Ralf Lämmel's lecture goes back to the roots, essentially revisiting Wadler's "The essence of functional programming"—the 1992 paper that discovered monads and popularized their use in functional programming. Ralf Lämmel's lecture and accompanying code distribution show Wadler's seminal insight: those original scenarios and observations still make sense today. Indeed, Simon Marlow (a Haskell/GHC high priest @ MSR Cambridge) recently noted: "it's still the best monad tutorial" (see http://twitter.com/simonmar/status/21397398061).

After months of negotiation and delay, Warner Brothers and Metro-Goldwyn-Mayer are on the verge of an agreement that would allow the director Peter Jackson to begin shooting a two-part version of J. R. R. Tolkien’s “The Hobbit” early next year.

Embedded systems designers deserve better than the feature-lacking point-tools available today. Embedded designs should be more than a collection of microcontrollers and discrete components, pulled together by board design tools and software development environments that are not aware of each other presence, let alone integrated together. Programmable devices are not new. Embedded software is older than most of us! And a lot of embedded design is highly focused on specific interaction between the software and peripherals. So why do we still not have tools that bring all this together and make our lives easier and more productive?

Rube Goldberg couldn’t have designed a more elegant confluence of convoluted causal relationships.  Start analyzing the perplexing paradox of the FPGA synthesis market and each link of the chain reveals a bizarre force vector that eventually doubles back onto itself into an unlikely equilibrium that miraculously has held stable for a full decade despite disruptive forces of epic proportions. For over a decade now, Synplify has navigated these waters and has continued to survive and thrive through the unlikeliest of conditions.  Now in the hands of EDA giant Synopsys, the Synplify family of FPGA synthesis tools continues to evolve - with a major upgrade this fall.  When you put a digital design into an FPGA, there are two technologies that determine whether your design fits or doesn’t fit, whether it meets your timing constraints or does not, whether the power consumption will be within your limits (or those of the FPGA), or whether it fails completely, leaving your project at the mercy of major mulligans.   Those two technologies are synthesis and place-and-route. 

IBM's light-powered links overcome the greatest speed bump in supercomputing: interconnect bandwidth

To paraphrase helicopter pioneer Igor Sikorsky: If you're in trouble, an airplane can fly over and drop flowers, but a helicopter can save your life. It can deftly maneuver through tight spots and alight in remote places. It can float next to a mountain to search for the lost. And the best sound a wounded soldier can hear is that telltale rotor beat, just minutes before being evacuated to a hospital. When roads are impassable, bridges have been destroyed, and the electricity has been knocked out, helicopters can still deliver supplies and rescue people.

In this session, Don McCrady discusses how C++ programmers can fully utilize multicore in their applications using the Concurrency Runtime (ConcRT), the Parallel Pattern Library (PPL), and the Asynchronous Agents Library that ship with Visual Studio 2010.

This article features an example chapter from a new *Hot-off-the-Press* book on FPGA Design that just recently hit the streets in August 2010. This chapter is reproduced here with the kind permission of the publisher – Springer. This book -- FPGA Design: Best Practices for Team-Based Design -- describes best practices for successful FPGA design. It is the result of the author’s meetings with hundreds of customers on the challenges facing each of their FPGA design teams. By gaining an understanding into their design environments, processes, what works and what does not work, key areas of concern in implementing system designs have been identified and a recommended design methodology to overcome these challenges has been developed.

Earlier in this series, we touched on one problem that can arise when sampling an analog signal, namely the problem of aliasing. There are three other issues with signal sampling to which we now turn our attention: digitization effects, finite register length effects, and oversampling. So far, weve assumed that all of the signals were measuring are continuous analog values; i.e., our measurements are completely accurate. Even in the cases in which we have noise, the underlying assumption is that the measurement itself, for example the noisy sensor output voltage, is known precisely.