[Jack Qiao] wanted an autonomous robot that could be handy around an ever-changing shop. He didn’t want a robot he’d have to baby sit. If he said, ‘bring me the 100 ohm resistors’, it would go find and bring them to him.
He iterated a bit, and ended up building quite a nice robot platform for under a thousand dollars. It’s got a realsense camera and a rangefinder from a Neato robotic vacuum. In addition to a mircrophone, it has a whole suite of additional sensors in its base, which is a stripped down robotic vacuum from a Korean manufacturer. A few more components come together to give it an arm and a gripper.
The thinking is done on a Nvidia Jetson TK1 board. The cores on the integrated graphics card are used to perform faster computer vision calculations. The software is all ROS based.
As can be seen in the video after the break. The robot uses SLAM techniques to successfully navigate and complete tasks such as fetch resistors, get water, and more. [Jack Qiao] is happy with his robot, and we would be too.
Continue reading “Hackaday Prize Entry: BunnyBot Helps Out All On Its Own”
Hackerboards got a chance to sit down with Intel’s latest attempt to turn hackers into a willing and steady revenue stream, the, “Euclid.” The board is cool in concept, a full mini computer with stereo cameras, battery, Ubuntu, and ROS nicely packaged together.
We would be more excited if we knew how much it costs, but in principle the device is super cool. From a robotics research perspective it’s a sort of perfect package. ROS is a wonderful distributed and asynchronous robotic operating system, test, and development platform. The Intel developers designed this unit around the needs of ROS and it comes pre-installed on the camera.
For those who haven’t used ROS before, this is a really cool feature. ROS is natively distributed. It really doesn’t care where the computer supplying its data lives. So, for example, if you already had a robot and wanted to add stereo vision to it. You could offload all the vision processing components of your existing ROS codebase to the Euclid and continue as if nothing changed.
The other option is to use the board as the entire robot brain. It’s self contained with battery and camera. It’s a USB to serial connection away from supercharging any small robotics project.
Unfortunately the board is still a demo, and based on Intel’s history, likely to be too expensive to lure ordinary hackers away from the RasPis and import cameras they already know how to hack together into more or less the same thing. Universities will likely be weak at the knees for such a development though.
Let’s face it: 3-dimensional odometry can be a computationally expensive problem often requiring expensive 3D cameras and optimized algorithms that can be difficult to wrap our head around. Nevertheless, researchers continue to push the bounds of visual odometry forward each year. This past year was no exception, as [Christian], [Matia], and [Davide] have tipped the scale in terms of speed with an algorithm that can track itself in 3D in real time.
In the video (after the break), the landmarks are sparse, the motion to track is relentlessly jagged, but SVO, or Semi-Fast Visual Odometry [PDF warning], keeps tracking its precision with remarkable consistency, making use of “high frequency texture” as a reference. Several other implementations require two cameras or a depth camera variant, but not SVO. It uses a single camera with a high frame rate between 55 and 300 frames per second. Best of all, the trio at the University of Zürich have made their codebase open source and available as a package for ROS.
Continue reading “Insanely-Quick 3D Tracking with 1 Camera”
“This is the year of the general purpose home robot!” “2016 is going to be for robots like 1976 was for the home computer!” The problem with statements like those is the fact that we’ve been hearing them since the 1970’s. General purpose home robots still have a long way to go. Sure, we’ve got Roomba, we’ve even got self-driving cars. But we don’t have Rosie from the Jetsons. And while I don’t think we’re going to get to Rosie for a while, there are some simple challenges that can spur development in that direction. One need look no further than one’s own laundry room.
Using machines to wash and dry laundry isn’t a new concept. Washers and dryers have become commonplace enough that we don’t think of them as robots. Hamilton Smith patented the rotary washing machine in 1858. Maytag has had home machines available for nearly 100 years. Many of the early machines were powered by gasoline engines, as electricity wasn’t common in rural farmhouses. Things have improved quite a bit since then! From the dryer we transfer our laundry to a basket, where it has to be folded. It is this final step that cries out for a homemaking automaton to take this chore out of Everyman’s hands.
As one can imagine, folding laundry is one of those tasks that is easy for humans, but hard for robots. However, it’s not impossible. The idea of this article is to show what has been done, and get people talking. A project like this would take a person or group of people with skills in mechanics, electronics, machine vision, and software. It would also be sure to place well in the 2016 Hackaday Prize.
Continue reading “The Challenges of A Laundry Folding Robot”
Remember Furby? The cute reactive robot was all the rage a few years ago, when the strange chattering creature was found under many a Christmas tree. Most Furbys have been sadly neglected since then, but the Open Furby project aims to give the toy a new lease of life, transforming it into an open source social robot platform.
We’ve featured a few Furby hacks before, such as the wonderful Furby Gurdy and the Internet connected Furby but the Open Furby project aims to create an open platform, rather than creating a specific hack. It works by replacing the brains of the Furby with a FLASH controller that runs the Robot Operating System (ROS), making the Furby much easier to program and control. They have also replaced the eyes with small OLED screens, which means it can do things like show a weather forecast, facebook notification, etc.
It is still in the early stages, but it looks like an interesting project. Personally, I am waiting for the evil Furby that wants to kill you and eat your flesh with that nasty beak…
Continue reading “Open Furby Opens The Furby”
French robot-artist [Lyes Hammadouche] tipped us off to one of his latest works: a collaboration with [Ianis Lallemand] called Texel. A “texel” is apparently a time-pixel, and the piece consists of eight servo-controlled hourglasses that can tip themselves over in response to viewers walking in front of them. Besides making graceful wavelike patterns when people walk by, they also roughly record the amount of time that people have spent looking at the piece — the hourglasses sit straight up when nobody’s around, resulting in a discrete spatial representation of people’s attentions to the piece: texels.
We get jealous when we see artists playing around with toys like these. Texel uses LIDAR scanners, Kalman-filtered naturally, to track the viewers. openFrameworks, OpenCV, and ROS. In short, everything you’d need to build a complex, human-interactive piece like this using completely open-source tools from beginning to end. Respect!
Continue reading “Texel: Art Tracks You, Tracks Time”
[DJI], everyone’s favorite — but very expensive — drone company just announced the Manifold — an extremely capable high performance embedded computer for the future of aerial platforms. And guess what? It runs Ubuntu.
The unit features a quad-core ARM Cortex A-15 processor with an NVIDIA Keplar-based GPU and runs Canonical’s Ubuntu OS with support for CUDA, OpenCV and ROS. The best part is it is compatible with third-party sensors allowing developers to really expand a drone’s toolkit. The benefit of having such a powerful computer on board means you can collect and analyze data in one shot, rather than relaying the raw output down to your control hub.
And because of the added processing power and the zippy GPU, drones using this device will have new artificial intelligence applications available, like machine-learning and computer vision — Yeah, drones are going to be able to recognize and track people; it’s only a matter of time.
We wonder what this will mean for FAA regulations…