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Their design enables managing the modules such that the modules are hot-swappable and, they said, easily replaceable. "Swap in and out any module in seconds." They added that no restart is needed when you connect a module. It will work straight away. They believe the future is modular—and in turn customizable. Each module has its own special feature. They see this watch as useful for different professions and lifestyles, including medical, academic and sports..
"The most amazing thing about BLOCKS is that the strap is made of several links (modules) each of which have their own functions. You can choose the modules you want to build a smartwatch unique to you." You choose modules, connect them and start building up your watch.
The team said you can swap a battery module if you notice that your is running low on power.
They have turned to Kickstarter for funding and they have received a quick and hefty response. Out of their goal to raise $250,000 they attracted at the time of this writing $406,595 with 36 days still left to go.
 
 
The core watch component has the features of most other smartwatches. At launch, the team will have users covered for all of the basic apps such as notifications, calendars and notes.
One key to the success of this modular watch will be the availability of modules that attract people to utilize this wearable. There would need to be a range of choices to suit different lifestyles and work environments.
BLOCKS has an open platform toward this end to allow developers and companies to create modules. The types can range from gaming, sports, to healthcare, to workplace or even experimental ones for academic research.
"We have already partnered with major tech companies," said the team, to develop more modules. They said they have more than 1,500 developers signed up. The Software Development Kit (SDK) and Module Development Kit (MDK) will be available soon. The Developers Kit will allow developing and testing modules with different sensors.
For $195 you get a BLOCKS core and strap and estimated delivery is May. For $275 you get a core and four modules of your choice. Estimated deliver is also May. After the campaign, they plan to get in touch will get in touch to ask what combination of modules backers would like.
BLOCKS will be compatible with both iPhones and Android smartphones. It works with iOS 8 and above, on iPhone 4s and above. It works with all Android 4.0+ phones including those from LG, Motorola, Sony, Samsung, HTC and Xiaomi.
BLOCKS watches are accompanied with an app that can be downloaded on any iOS or Android device. The app enables you to customize watchfaces, download apps for your BLOCKS watch and select the notifications you want to receive.
BLOCKS is based in London. Close to half of the team are PHD students at Imperial College in mechanical engineering and computer science. The team also includes electrical engineers and product designers.
Researchers at Georgia Tech have identified a way to teach robots how to fall with grace and without serious damage. The work is important as costly robots become more common in manufacturing alongside humans. The skill becomes especially important, too, as robots are sought for health care or domestic tasks – working near the elderly, injured, children or pets.
Ph.D. graduate Sehoon Ha and Professor Karen Liu developed a new algorithm that tells a  how to react to a wide variety of  – from a single step to recover from a gentle nudge, to a rolling motion that breaks a high-speed fall. As a result, robots can minimize the damage or injury they might cause to themselves or others while falling by learning the best sequence of movements to slow their momentum. The planning algorithm was validated in physics simulation and experimentally tested on a BioloidGP humanoid.
"A fall can potentially cause detrimental damage to the robot and enormous cost to repair," said Ha, who graduated in summer 2015 and is now a postdoctoral associate at Disney Research Pittsburgh in Pennsylvania. "We believe robots can learn how to fall safely. Our work unified existing research about how to teach robots to fall by giving them a tool to automatically determine the total number of contacts (how many hands shoved it, for example), the order of contacts, and the position and timing of those contacts. All of that impacts the potential of a fall and changes the robot's response."
With the latest finding, Ha builds upon Liu's previous research that studied how cats modify their bodies in the midst of a fall. Liu knew from that work that one of the most important factors in a fall is the angle of the landing. She also knew that a well-designed robot has the "brain" to compute a softer landing, but hadn't yet optimized the sequence of motions that take place during a fall, like she and Ha were able to do in their latest research.
 
 
"From previous work, we knew a robot had the computational know-how to achieve a softer landing, but it didn't have the hardware to move quickly enough like a cat," Liu said. "Our new planning algorithm takes into account the hardware constraints and the capabilities of the robot, and suggests a sequence of contacts so the robot gradually can slow itself down."
Now the robots may fall more gracefully than people and possibly cats, too. Imagine that.
The research, entitled "Multiple Contact Planning for Minimizing Damage of Humanoid Falls," was presented this month at the IEEE/RSJ International Conference on Intelligent Robots and Systems in Hamburg, Germany.
 
 
In the video, the top robot uses a novel algorithm to minimize impact when the robot falls. The algorithm is not used for the robot on the bottom of the screen.