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Getting a grip on robotic grasp
Date:7/17/2014

tain gestures such as grabbing an apple may differ slightly from person to person, and ultimately, a robotic aid may have to account for personal grasping preferences. To that end, she envisions developing a library of human and robotic gesture correlations. As a user works with the robot, it could learn to adapt to match his or her preferences, discarding others from the library. She likens this machine learning to that of voice-command systems, like Apple's Siri.

"After you've been using it for a while, it gets used to your pronunciation so it can tune to your particular accent," Wu says. "Long-term, our technology can be similar, where the robot can adjust and adapt to you."

Down the road, Asada says the robot may also be scaled down to a less bulky form.

"This is a prototype, but we can shrink it down to one-third its size, and make it foldable," Asada says. "We could make this into a watch or a bracelet where the fingers pop up, and when the job is done, they come back into the watch. Wearable robots are a way to bring the robot closer to our daily life."


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Contact: Sarah McDonnell
s_mcd@mit.edu
617-253-8923
Massachusetts Institute of Technology
Source:Eurekalert  

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