From mowing the lawn to tracking hurricanes and providing therapeutic treatments, robots are undoubtedly becoming an integral part of the way we do things. But to help these machines interact effectively with their environment, engineers need to provide them with artificial intelligence tools that can help them recognize the things they may encounter.
Enter a new crowdsourcing project that makes it easy for people with a Microsoft Kinect motion-sensing device to make 3D scans of anything and everything around them. Robotics engineers plan to create a catalog of scans that will help them design intelligence tools into robots.
The Website for the Kinect@Home project asks volunteers to "help the robots." Using their Kinect, volunteers produce 3D models that can be shared on the site or with friends, embedded into other Websites, or imported into 3D modeling software to be used in other applications.
The project provides instructions, a plug-in, drivers, and installation software. Once the software is installed on a local computer, people can point their Kinect at whatever they want to scan and begin creating their models.
Microsoft released the first Kinect for its Xbox 360 video game console in late 2010. A version for Windows came out early this year. Microsoft has sold more than 18 million copies of the device, which lets people interact with the Xbox or a Windows PC using gestures and spoken commands.
Although image data storage isn't exactly small or cheap in terms of memory required, I think the basic idea here is analogous to that of machine vision image libraries, where the machine vision user builds up a database of images of objects to be inspected on the line, such as PC boards and components on the boards.
That makes sense. Those image libraries must get huge and there must be some sort of mechanism in place for sharing and collaboration so engineers aren't reinventing the wheel over and over again.
The idea is to create 3D scans of various objects to help teach robots about their environment and the objects in it, so they can navigate the environment and manipulate those objects, including, for example, refrigerators and people. An example given in this IEEE Spectrum article http://spectrum.ieee.org/automaton/robotics/robotics-hardware/kinecthome-wants-to-start-3d-scanning-the-world?utm_source=feedburner&utm_medium=feed&utm_campaign=Feed:+IeeeSpectrum+(IEEE+Spectrum) is teaching a robot to open a fridge door. First, the robot has to have a map of a fridge door and how it operates. If the robot is Kinect-equipped, as many now are (in R&D, anyway), it can use 3D images for those maps. But fridges aren't all the same size, don't have the same kind of door, and doors aren't always located on the same side of the box. So it needs an image library for each object: lots and lots of images.
This is an interesting project. The Kinect is an interesting device, and has many uses. Building up a database in this way is an outstanding way to get a large mass of information in a short time. In AI it is very beneficial to have a large training set. Frankly, this is true of us humans as well.
Looks pretty cool and I like the crowdsourcing angle a ton, but I'm not really sure what kinds of scans are being collected with the Kinect. It is scans of people, physical objects, movements? I'm also curious how this data is being fed back to robotics designers for future use? My guess is through the site community, but just wanted to confirm.
A new battery design, which replaces lithium with abundant and low-cost elemental sulfur, is still in its nascent stages but shows real promise for giving batteries more energy potential.
The push to achieving more intelligent, integrated manufacturing is putting a strong focus on networking and connectivity as key enabling technologies.
Now that solar and wind harvesting technologies are a thriving market, researchers are seeking other environmentally related energy sources for which they can create harvesting devices.
Surveillance, reconnaissance, and search and rescue in military and first responder situations are popular applications for aerial robots. Yet not all the robots are considered unmanned aerial vehicles.
From Dell / Intel® New Paradigms in Design Work Scott Hamilton, vertical market strategist for Dell Precision workstations, 5/2/2013 5
Early in my career, I worked as a draftsman and remember the days of drawing on vellum with numbered pencils and Mylar with plastic lead. This was a fun experience in the sense that I ...
I've been using workstations for more than 10 years and love finding ways to get more performance from my system. With demanding professional applications that require more power each ...
A lasting memory from my first job as an engineer in an auto assembly plant is standing on hard concrete at six in the morning, vending-machine coffee clutched in hand, listening to ...
For industrial control applications, or even a simple assembly line, that machine can go almost 24/7 without a break. But what happens when the task is a little more complex? That’s where the “smart” machine would come in. The smart machine is one that has some simple (or complex in some cases) processing capability to be able to adapt to changing conditions. Such machines are suited for a host of applications, including automotive, aerospace, defense, medical, computers and electronics, telecommunications, consumer goods, and so on. This radio show will show what’s possible with smart machines, and what tradeoffs need to be made to implement such a solution.
To save this item to your list of favorite Design News content so you can find it later in your Profile page, click the "Save It" button next to the item.
If you found this interesting or useful, please use the links to the services below to share it with other readers. You will need a free account with each service to share an item via that service.
Tweet This
7 
