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AdvancedManufacturing.org


“It is believed that the present meta-skin technology will find many applications in electromagnetic frequency tuning, shielding and scattering suppression,” the engi- neers wrote in their paper, published in Scientific Reports. Associate Prof. Liang Dong and Prof. Jiming Song were


hoping to prove that electromagnetic waves—perhaps even the shorter wavelengths of visible light—can be sup- pressed with flexible, tunable liquid-metal technologies. What they came up with are rows of split ring resonators embedded inside layers of silicone sheets. The electric resonators are filled with galinstan, a metal alloy that’s liquid at room temperature and less toxic than other liquid metals such as mercury. Those resonators are small rings with an outer radius of 2.5 millimeters and a thickness of half a millimeter. They have a 1-mm gap, essentially creating a small, curved segment of liquid wire. The rings create electric induc- tors and the gaps create electric capacitors. Together they create a resonator that can trap and suppress radar waves at a certain frequency. Stretching the meta-skin changes the size of the liquid metal rings inside and changes the frequen- cy the devices suppress. Tests showed radar suppression


was about 75% in the frequency range of 8 to 10 gigahertz, according to the paper. When objects are wrapped in the meta-skin, the radar waves are suppressed in all incident directions and observation angles. “Therefore, this meta-skin technology is different from traditional stealth technologies that often only re- duce the backscattering, i.e., the power reflected back to a probing radar,” the engineers wrote in their paper. The idea is that this meta-skin could one day coat the next generation of stealth aircraft.


R


Robot hand learns to get a grip


obots today are capable of many tasks, but intricate movements that require dexterous in-hand manipu- lation—rolling, pivoting, bending, sensing friction and other things humans do effortlessly with our hands— have proved difficult. A team of computer scientists and engineers from the University of Washington built a five-fingered robot hand


that can both perform dexterous manipulation and learn from its experience without needing humans to direct it. “Hand manipulation is one of the hardest problems that


roboticists have to solve,” said Vikash Kumar, the lead author. “A lot of robots today have pretty capable arms but the hand is as simple as a suction cup or maybe a claw or a gripper.” The UW team spent years developing the hand, as well as a simulation model that enables a computer to analyze movements in real time. In their latest demonstration, they apply the model to the hardware and real-world tasks like rotating an elongated object. With each attempt, the robot hand gets progressively


more adept at spinning the tube, thanks to machine learn- ing algorithms that help it model both the basic physics involved and also plan which actions it should take to achieve the desired result. The more challenging aspect was designing a hand with enough speed, strength, responsiveness and flexibility to


This five-fingered robot hand can learn how to perform dexterous manipulation on its own, rather than having humans program its actions.


mimic the basic behaviors of a human hand. The end result was a Shadow Hand skeleton actuated with a custom pneumatic system, which can actually move faster than a human hand. With a cost of $300,000, it’s too expensive for routine commercial or industrial use, but allows the researchers to test innovative control strategies. Most recently, the research team has transferred the


software simulation model to work on the actual five-fin- gered hand hardware. As the robot hand performs differ- ent tasks, the system collects data from various sensors and motion-capture cameras and employs machine learn- ing algorithms to continually refine and develop more re- alistic models. The next trials will focus on global learning and challenge the hand to manipulate an unfamiliar object. The findings were presented at the 2016 IEEE Interna- tional Conference on Robotics and Automation.


15


Photo courtesy University of Washington


Summer 2016


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