Robot Performing A Tightrope Act

This robot is able walk the tightrope (translated). Well, it’s more of a shuffle than a walk, but still a lot better than we could do.

In the video after the break you can see the bot starting on the platform to the right. As it steps out onto the wire (which rides in a groove on the bottom of its foot) the robot spreads its arms to help maintain balance. When the other foot leaves the platform that is the last stride we will see until it reaches the other side. The rest of the act consists of sliding the feet a little bit at a time until it gets all the way across.

[Dr. Guero] has been working on at least one other balancer as well. Also embedded after the break is a robot riding a bicycle. It actually puts a foot down when stopped, and gives a stuttering push-off to get going again. This guy would be right at home riding past you in the hallways of the Death Star.

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Tank Tread Robot Build Aims For A Smooth Ride

There’s all kinds of interesting things going into this tank robot build, but that beautiful suspension system immediately caught our eye. It helps to protect the body of the robot from being shaken apart when traveling over rough surfaces. Make sure to check out the four parts of the build log which are found on the left sidebar at the post linked above.

This a Master’s thesis project and has been built from common parts. The motors for the treads are pulled from a pair of cordless drills, with some capacitors added to help combat the draw when they start up. The treads themselves are each made from a pair of bicycle chains connected with numerous PVC pipe segments. The curved section of each PVC piece goes toward the chain, leaving the edges toward the ground for great traction. The tree wheels which support the middle of the tread each have a hinge and spring to absorb the shock of running full speed into concrete sidewalk corners like we see in the video after the break.

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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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