Controlling A Robot With Your Mind

For [Ern]’s MEng group project, his group had to develop a robotics platform capable of achieving some end goal. Because innovation is a large part of the grade, [Ern] convinced his team members to work with a brain controlled interface and build a mind controlled robotics platform.

For wont of having an easy build, [Ern] and his team chose a Lynxmotion Tri-Track robot capable of moving around the classroom while receiving commands from a computer. The mind-control portion of the build comes from a NeuroSky MindWave Mobile, a cheap and fairly open EEG system that reads alpha, beta, and delta waves generated by a user’s brain and sends that data over to a computer for processing.

After a bit of testing that included an Arduino to move the robot forward if the MindWave’s ‘attention’ value was over 60%, [Ern] and his team looked for a way to implement multi-directional control.

In order to get the robot moving left, right, and backwards in addition to moving forwards, the team looked at the included ‘blink detection’ abilities of the MindWave to cycle through a few commands. This technique turned out to be far too sensitive – the blink detection of the MindWave is simply too good. To get around that problem, the team used the signal strength of the received EEG signals. The theory being when a user blinks their eyes, the EEG contacts will move slightly, degrading the signal received by the hardware.

The team finally got a reasonable mind-controlled robot up and working, as demonstrated in the video after the break. Check out how each blink allows [Ern] and his colleagues to cycle through driving modes. Pretty neat for controlling something with your mind.

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Have A Baby? Build Another One!

Ever since his daughter was born, [Markus] has been keeping logs full of observations of human behavior. Despite how it sounds, this sort of occurrence isn’t terribly odd; the field of developmental psychology is filled with research of this sort. It’s what [Markus] is doing with this data that makes his project unique. He’s attempting to use stochastic learning to model the behavior of his daughter and put her mind in a robot. Basically, [Markus] is building a robotic version of his newborn daughter.

The basics of stochastic learning (PDF with more info) is that a control system is modeled on an existing system – in this case, a baby – by telling a robot if it is doing a good or bad job. Think of it as classical conditioning for automatons that can only respond to a 1 or 0.

[Markus] built a robotic platform based on an Arduino Mega and a few ultrasonic distance sensors. By looking at its surrounding environment, the robot makes judgments as to what it should do next. In the video after the break, [Markus] shows off his robot finding its way around an obstacle course – really just a pair of couch cushions.

It’s a long way from crawling around on all fours, paying attention to shiny things, and making a complete mess of everything, but we’re loving [Markus]’ analytical approach to creating a rudimentary artificial intelligence.

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Using UAVs To Find Mannequins Lost In The Outback

Every other year the Australian Research Center for Aerospace Automation, the government of Queensland, Australia  and other government and research institutions hold a contest to develop technology for unmanned aerial vehicles for the wastes of central Australia. Canberra UAV – a group of autonomous drone enthusiasts from the Make, Hack, Void hackerspace – took part in this UAV challenge this year. They ended up with one of the most successful UAVs to every compete, and while they didn’t quite finish the competition they were one of the most successful entries to date.

The goal of the Search and Rescue Outback Challenge is to take off from a landing strip, search for a mannequin named Outback Joe, and deliver 500 ml of life-giving water via air drop. Out of 72 teams entered in to this year’s Outback Challenge, only 6 were allowed to take off – safety restrictions, don’t you know – and all but two hadn’t been destroyed via ‘rapid, unplanned descent’ during qualifications.

UAV Canberra was the only team able to search the entire 5 nautical mile radius search area with their cameras and find Outback Joe. Contest judges gave them permission to drop their payload, but unfortunately the bottle of water was snagged on the engine.

In the many iterations of the Search and Rescue Outback Challenge, UAV Canberra is only the second team to locate a mannequin in the outback, and the first to do it autonomously. A shame, then, that they were unable to claim a victory, but we’ll look forward to their entry in the next Search and Rescue competition.

You can check out a few videos of the Canberra UAV team’s flights after the break.

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200 Pound, WiFi Deploying Robot Ran Over My Foot

[Adam Bercu] and [Dan Landers] from Artisan’s Asylum in Somerville, MA brought a very, very cool toy to Maker Faire this year. It’s a two hundred pound WiFi repeater deploying robot able to amble across unforgiving terrain and my foot.

The robot is controlled through a web interface with the help of a front-mounted web cam with pan and tilt controls. All the signals are sent through a WiFi connection to a node.js web server; not the best way to communicate with a robot over long distances, but [Adam] and [Dan] have a few tricks up their sleeve.

On the back of the robot are two Pelican cases loaded up with a battery and a Linksys WRT54G wireless router. When the robot reaches the limits of its range, it activates a solenoid, dropping a WiFi repeater. This repeater has enough battery juice to stay powered for about a day and a half, meaning the robot can make multiple trips to deploy a wireless network through some very hostile terrain. Perfect for disaster and search and rescue operations.

There are two videos after the break: the first is [Dan] going over the capabilities of his tank bot and the second is a short demo of the bot tearing up the grass at Maker Faire.

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Intelligent Autonomous Vehicle Makes It To Maker Faire

A few guys from Rutgers showed up at Maker Faire with Navi, their vehicle for the 2012 Intelligent Ground Vehicle Competition. Powered by two huge lead acid batteries, Navi features enough high-end hardware to hopefully make it through or around just about any terrain.

Loaded up with a laser range finder, a stereo camera setup, compass, GPS receiver, and a pair of motors capable of pulling 40A, Navi has the all the hardware sensors required to make it around a track with no human intervention. Everything is controlled by a small netbook underneath the control panel, itself loaded up with enough switches and an 8×32 LED matrix to be utterly incomprehensible.

In the videos after the break, the guys from Rutgers show off the systems that went into Navi. There’s also a video showing off Navi’s suspension, an impressive custom-built wishbone setup that will hopefully keep Navi on an even keel throughout the competition.

Also of note: A PDF design report for Navi and Navi’s own blog.

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Professional Looking Dog Robot Was Actually [Martin’s] Master’s Thesis

If you think this thing looks good you should see it move. [Martin Smith] hit a home run on the project, which was his Master’s Thesis. Fifteen servo motors provide a way for the bot to move around. Having been modeled after a small canine the gait is very realistic. The tail is even functional, acting as a counterweight when moving the legs.

The project was meticulously built in a 3D environment before undertaking any physical assembly. The mechanical parts are all either milled from aluminum or 3D printed. Two mBed boards mounted on its back allow it to interact with its environment. One of them handles image processing, the other drives the array of motors. And of course it doesn’t hurt that he built some Larson Scanners in as eyes.

Don’t miss the video after the break which shows off the entire project from planning to demonstration. We can’t help but be reminded of the rat-thing from Snow Crash.

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Whatever A Phobia Of Fingers Is Called, This Is It.

[youtube=http://www.youtube.com/watch?v=7LSXvhLKjCU&w=470]

Touched is a project by [Rebecca Strauss] that integrates servos, strings, and felt into a horrifying kinetic sculpture made up of a dozen mechanical fingers straight from a Boschian nightmare.

The fingers are made up of segments of wood articulated with the help of a small string. Each pair of fingers is controlled by a single servo, and the tips of each pair of fingers is controlled by a second servo.

After covering them in felt, [Rebecca] wrapped conductive thread around each of the fingers. When some of the fingers are touched, they all recoil as if controlled by a demon living just under a mountain of felt.

[Rebecca] brought in another kinetic sculpture using her servo controlled fingers; in the video up at the top and after the break, you can see the inner workings of this floor-mounted version. When the IR proximity sensor goes off, the fingers recoil but can be coaxed out again by gently stroking one of the phalanges.

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