How do you get teenagers interested in science, technology, and engineering? [Erich]’s team at the Lucerne University of Applied Sciences makes them operate three robots to get a gumball. The entire demonstration was whipped together in a few days, and has been field-repaired at least once; a green-wire fix was a little heavy on the solder and would short out to a neighboring trace when mechanical force was applied.
Continue reading “Mintomat: An Overcomplicated Gumball Machine”
It’s no secret that we love bizarre robot locomotion, so we are naturally suckers for BALLU (YouTube link, also embedded below) the Bouyancy-Assisted Lightweight Legged Unit. The project started with a simple observation — walking robots are constrained by having to hold themselves up — and removing that constraint make success much easier. Instead of walking, BALLU almost floats and uses what little net weight it does have to push against the ground.
It’s getting easier and easier to add machine intelligence to your hacks, even to the point where you sometimes don’t have to install any special software. In this case [Dexter Industries] has added the ability to read human emotions to their EmpathyBot robot by making use of Google Cloud Vision.
Press a button on the robot and it moves forward until it’s a certain distance from an object. It then takes a picture and sends it off to Google Cloud Vision along with a request to do face detection. The response that Google returns is in JSON format and, if it finds a face, includes the likelihood of the face being happy, sad, sorrowful or surprised. The robot parses that response and gives an appropriate canned speech using the text-to-speech software, eSpeak e.g. “You seem happy! Tell me why you are so happy!”.
[Dexter] has made the source code available on github. It’s written in python and is easy to read by anyone with even just a little programming experience. The video after the break gives a number of demonstrations, including some with non-human subjects.
Continue reading “Raspberry Pi Robot That Reads Your Emotions”
Most inexpensive 3D printers use a type of lead screw to move some part of the printer in the vertical direction. A motor turns a threaded rod and that causes a nut to go up or down. The printer part rides on the nut. This works well, but it is slower than other drive mechanisms (which is why you don’t often see them on the horizontal parts of a printer). Some cheap printers use common threaded rod, which is convenient, but prone to bad behavior since the rods are not always straight, the threads are subject to backlash, and the tolerances are not always the best.
More sophisticated printers use ACME threaded rod or trapezoidal threaded rods. These are made for this type of service and have thread designs that minimize things like backlash. They typically are made to more exacting standards, too. Making the nut softer than the rod (for example, brass or Delrin) is another common optimization.
However, when lead screws aren’t good enough, mechanical designers turn to ball screws. In principle, these are very similar to lead screws but instead of a nut, there is a race containing ball bearings that moves up and down the screw. The ball bearings lead to less friction.
Misumi recently posted a few blog articles about ball screws. Some of the information is basic, but it also covers preloading and friction. Plus they are promising future articles to expand on the topic. If you prefer to watch a video, you might enjoy the one below.
Australian roboticists from the Queensland University of Technology have developed a prototype agricultural robot that uses machine vision to identify both weed and crop plants before either uprooting or poisoning the weeds or applying fertiliser to the crop.
The machine is a wide platform designed to straddle a strip of the field upon which it is working, with electric wheel motors for propulsion. It is solar-powered, and it is envisaged that a farm could have several of them continuously at work.
At a superficial level there is nothing new in the robot, its propulsion, or even the plant husbandry and weeding equipment. The really clever technology lies in the identification and classification of the plants it will encounter. It is on the success or failure of this in real farm environments that the robot’s future will hinge. The university’s next step will be to take it on-farm, and the ABC report linked above has a wonderfully pithy quote from a farmer on the subject. You can see the machine in action in the video below the break.
Farming robots have a significant following among the hardware hacker community, but it is possible that the machine-vision and plant-identifying abilities of this one would be beyond most hackers. However it is still an interesting project to watch, marking as it does a determined attempt to take the robot out of the lab and into real farm settings.
It’s that time of year again. The nights are getting longer and the leaves are turning. The crisp fall air makes one’s thoughts turn to BattleBots: pumpkin-skinned BattleBots.
If you’re asking yourself, “could a laser-cut plywood bot, sheathed in a pumpkin, stand up against an all-metal monster”, you haven’t seen BattleBots before. Besides the hilarious footage (see video embedded below), a lot of the build is documented, from making a CAD model of a pumpkin to laser-cutting the frame, to “testing” the bot just minutes before the competition. (That has to be a good idea!)
The footage of the pumpkinbot’s rival, Chomp, is equally cool. We love that the hammer weapon is accelerated so quickly that Chomp actually lifts in the air, just as Newton would have predicted. We’re not sure if the fire weapon is good for anything but show, and facing plywood pumpkinbots, but we love the effect.
Continue reading “Don’t Make Your Battlebot Out Of A Pumpkin”
What’s going through the mind of those your autonomous vacuum cleaning robots as they traverse a room? There are different ways to find out such as covering the floor with dirt and seeing what remains afterwards (a less desirable approach) or mounting an LED to the top and taking a long exposure photo. [Saulius] decided to do it by videoing his robot with a fisheye lens from near the ceiling and then making a heatmap of the result. Not being satisfied with just a finished photo, he made a video showing the path taken as the room is being traversed, giving us a glimpse of the algorithm itself.
The robot he used was the Vorwerk VR200 which he’d borrowed for testing. In preparation he cleared the room and strategically placed a few obstacles, some of which he knew the robot wouldn’t get between. He started the camera and let the robot do its thing. The resulting video file was then loaded into some quickly written Python code that uses the OpenCV library to do background subtraction, normalizing, grayscaling, and then heatmapping. The individual frames were then rendered into an animated gif and the video which you can see below.
Continue reading “A Glimpse Into The Mind Of A Robot Vacuum Cleaner”
