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Robots can now find hidden objects by radio waves

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  • Apr 01,2024
  • 2 min read
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For decades, radio frequency (RF) identification has been used to track everything from library books to pets. RF identification systems have two main components: a reader and a tag. The tag is a tiny computer chip that gets attached to — or, in the case of pets, implanted in — the item to be tracked. The reader then emits an RF signal, which gets modulated by the tag and reflected back to the reader.

At some point in your life, you’ve probably used a combination of sight and touch to find something hidden beneath your couch cushions. And for a while now, robotics researchers have tried to give their creations that same capability.

Ideology

MIT researchers developed a picking robot that combines vision with radio frequency (RF) sensing to find and grasp objects, even if they’re hidden from view. The technology could aid fulfillment in e-commerce warehouses.

The robot initiates the seek-and-pluck process by pinging the target object’s RF tag for a sense of its whereabouts. “It starts by using RF to focus the attention of vision,” says Adib. “Then you use vision to navigate fine maneuvers.”  

The technology behind it!

RF Grasp proved its efficiency in a battery of tests. Compared to a similar robot equipped with only a camera, RF Grasp was able to pinpoint and grab its target object with about half as much total movement. “RF is such a different sensing modality than vision,” says Rodriguez. “It would be a mistake not to explore what RF can do.”

                                                                                       

Working

The reflected signal provides information about the location and identity of the tagged item. The technology has gained popularity in retail supply chains — Japan aims to use RF tracking for nearly all retail purchases in a matter of years. The researchers realized this profusion of RF could be a boon for robots, giving them another mode of perception. “The robot has to decide, at each point in time, which of these streams is more important to think about,” says Boroushaki. “It’s not just eye-hand coordination, it’s RF-eye-hand coordination. So, the problem gets very complicated.”

Conclusion

In contrast to your typical college robotics undertaking, there is a clear use case for this invention too. The aptly named RF Grasp depends on a wrist-mounted camera and an RF reader to hone in and pick up an object. As long an item has an RF tag on it, the robot can find it, even if it's hidden behind things like wrapping paper. The workforce sees RF Grasp serving to corporations like Amazon additional automate and streamline their warehouses.


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I'm a Computer Science graduate, likes to do ordinary work in an extraordinary manner. I'm quite creative, a workaholic. I regularly used analyze new research, development, innovation by tech giants. I'm interested in Machine learning, Data Science along with research work applications on them & solving puzzles, quizzes.

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