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Algorithm Controls

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A subject plays a computer game as part of a neural security experiment at the University of Washington.
Patrick Bennett, CC BY-ND

By Eran Klein, University of Washington and Katherine Pratt, University of Washington


In the 1995 film “Batman Forever,” the Riddler used 3-D television to secretly access viewers’ most personal thoughts in his hunt for Batman’s true identity. By 2011, the metrics company Nielsen had acquired Neurofocus and had created a “consumer neuroscience” division that uses integrated conscious and unconscious data to track customer decision-making habits. What was once a nefarious scheme in a Hollywood blockbuster seems poised to become a reality.


In this episode, Audrow Nash and Christina Brester conduct interviews at the 2016 International Association of Science Parks and Areas of Innovation conference in Moscow, Russia. They speak with Vadim Kotenev of Rehabot and Motorica about prosthetic hands and rehabilatative devices; and Vagan Martirosyan, CEO of TryFit, a company that uses robotic sensors to help people find shoes that fit them well.

Lecturer Steffen Pfiffner of University of Weingarten in Germany is teaching ROS to 26 students at the same time at a very fast pace. His students, all of them within the Master on Computer Science of University of Weingarten, use only a web browser. They connect to a web page containing the lessons, a ROS development environment and several ROS based simulated robots. Using the browser, Pfiffner and his colleague Benjamin Stähle, are able to teach how to program with ROS quickly and to many students. This is what Robot Ignite Academy is made for.

Dig below the surface of some of today’s biggest tech controversies and you are likely to find an algorithm misfiring. These errors are not primarily caused by problems in the data that can make algorithms discriminatory, or their inability to improvise creatively. No, they stem from something more fundamental: the fact that algorithms, even when they are generating routine predictions based on non-biased data, will make errors. To err is algorithm.

interview by and   -   May 13, 2017

In this episode, Audrow Nash and Christina Brester conduct interviews at the 2016 International Association of Science Parks and Areas of Innovation conference in Moscow, Russia. They speak with Roman Luchin, CEO of CyberTech Labs., about a robotics development platform called Trik. Trik is intended to be an intermediate step when learning about robotics between Lego Mindstorms and programming on an embedded platform. Trik allows users to program with a graphical interface by ordering blocks. These blocks contain code in several common programming languages (python, F#, Pascal, etc.) and the code can be modified directly.

This is the second of three interviews from the conference.

by   -   May 10, 2017

MIT CSAIL approach allows robots to learn a wider range of tasks using some basic knowledge and a single demo.

Would you like to make a robot to grasp something, but you think that is impossible to you just because you can’t buy a robot arm? I’m here to tell that you can definitely achieve this without buying a real robot. Let’s see how:

In this video, Philip “Robo-Phil” English offers a tutorial on programming your NAO robot for human interation. Enjoy!

Imagine how easy it would be to learn skating, if only it doesn’t hurt everytime you fall. Unfortunately, we, humans,  don’t have that option. Robots, however, can now “learn” their skills on a simulation platform without being afraid of crashing into a wall. Yes, “it learns“! This is possible with the reinforcement learning algorithms provided by OpenAI Gym and the ROS Development Studio.

by   -   April 29, 2017

Engineers and researchers are already speculating about the next phase of UI development, especially for robotics control. So far, the leading candidate is gesture-based control—the use of physical gestures to relay commands.

Northwestern University mechanical engineering professor Todd Murphey and his team are engineering robots that one might say could make robotic assistance as seamless as “humanly” possible. With support from the National Science Foundation (NSF), the team is using novel algorithmic tools, such as a drawing robot, to develop the algorithms, or rules of behavior, that would greatly enhance a robot’s ability to adapt to human unpredictability.

interview by   -   March 18, 2017

In this episode, Audrow Nash interviews Bradley Knox, founder of bots_alive. Knox speaks about an add-on to a Hexbug, a six-legged robotic toy, that makes the bot behave more like a character. They discuss the novel way Knox uses machine learning to create a sense character. They also discuss the limitation of technology to emulate living creatures, and how the bots_alive robot was built within these limitations.

by   -   March 15, 2017

If you take humans out of the driving seat, could traffic jams, accidents and high fuel bills become a thing of the past? As cars become more automated and connected, attention is turning to how to best choreograph the interaction between the tens or hundreds of automated vehicles that will one day share the same segment of Europe’s road network.

You probably know the Sphero robot. It is a small robot with the shape of a ball. In case that you have one, you must know that it is possible to control it using ROS, by installing in your computer the Sphero ROS packages developed by Melonee Wise and connecting to the robot using the bluetooth of the computer.

by   -   March 13, 2017

Automated cars are hurtling towards us at breakneck speed, with all-electric Teslas already running limited autopilot systems on roads worldwide and Google trialling its own autonomous pod cars. However, before we can reply to emails while being driven to work, we have to have a foolproof way to determine when drivers can safely take control and when it should be left to the car.

Deep Learning in Robotics
June 24, 2017

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