It’s not every day that elephants inspire technological advances, let alone make existing technologies safer. Robotic arms can be quite dangerous, a single malfunction can cause frantic motion that could easily cause severe damage to us poor biological creatures. But the robotic arm ISELLA is built to minimize potential of such malfunction, and it’s design is inspired by an elephant’s trunk.
In my post on what makes a robot look feminine, a friend of mine posed an interesting observation in the comments. He felt too much time was being spent on humanoid development. He’d rather have development focus on non-humanoids that are useful now, at his home, than watching prototype humanoid robots through a glass window at the lab (not his words, I’m adding a bit of color). While this is a very understandable opinion, it’s based on a false assumption: Time spent on humanoids is miniscule in comparison to the entire range of robotics.
As of today, the city of Perm in Russia has a robot policeman patrolling the streets. The robot, named R BOT 001 (I wonder who picked the name) is a 250kg and 180cm high. The best part is that the robot is getting official rank. He is currently a trainee, but will soon become a cadet.
I’m really excited to see the details, which I’m should emerge in the next few days when the major newssites pick up on the story.
[via News.com.au, Image credit: Technovelgy]
When working on any software system there are various challenges. When a system is entirely new, there’s a ton. Here’s a short and generalized description of what’s involved in the process. In the interest of keeping this non-technical, let’s use some analogies of adventure and countryside (that we’re ruining with dams to power our systems, ironically). A system is a specific place that you want to go to, like Grandma’s Secret Hillside Bakery. The path that that leads to it are parts of the program you have to create.
What’s cheaper than a miniaturized, flying insect-like robot controlled by artificial intelligence? A miniaturized computer chip embedded as a control device in a natural organism. One of DARPAs projects involves injecting a chip into a Moth during the larva stage, the larva effectively adapting to the chip as part of its body. Once the moth hatches, machine learning is used to control it — to translate the signals and responses from the moth’s organic body — and effectively making it a mechorganic hybrid spy device; a cyborg moth.
It doesn’t seem too long until humanoid robots for the home become as advanced as Sony’s late QRIO, judging by the humanoid robot RoGun from the Korean company KornTech. This impressive robot is one of the latest models from Korea, and needless to say, sports some of the latest of technological innovations in the fields of robotics and A.I. I talked with the company’s marketing director, Lee Jea-Hyun, to provide you with an in-depth article on this new and very impressive humanoid.
Just when you think Hiroshi Ishiguro is busy amplifying the uncanny valley effect of one of his previous androids, he rolls out a new model. This time, it’s a gigantic bionic baby. Boasting about 200 sensors (optical, auditory and tactile) and 51 air actuators — the 1.3 meter tall robot is designed to mimic the physical motions of a two year old.
For some reason I’ve always had a special fear towards HIV of all diseases. Perhaps I was subjected to a wave of contraception propaganda run amok in my younger years, or heard one too many news of lunatics placing infected needles in theatre seats. In any case, I’m glad (albeit not surprised) to hear expectations for my chosen field of study to contribute significantly to AIDS research in the coming years.
Now we know. Cross a genetic algorithm with your favorite toy from childhood (Lego!) and you get intelligent, biologically reminiscent structures. Dr. Pablo Funes and his team at the Dynamical & Evolutionary Machine Organization devised a very cool simulator that can be told to create Lego structures of various kinds, such as bridges, using evolutionary algorithms. The creative aspect provides interesting food for thought: the system is given a goal and the solution design is entirely dependant on the machine.
I just put together a YouTube Think Artificial Channel as an experiment. For those unfamiliar Channels, they are a user’s collection of videos (neatly categorized) that others can view and subscribe to. Up until this point I hadn’t used YouTube channels, but seeing as I often post YouTube videos, I thought it might as well be good to actually keep a collection of them all in one place — along with the various videos I like but don’t get around blogging about.
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