{"id":20320,"date":"2021-04-02T12:59:26","date_gmt":"2021-04-02T07:14:26","guid":{"rendered":"https:\/\/www.revoscience.com\/en\/?p=20320"},"modified":"2021-04-02T13:09:22","modified_gmt":"2021-04-02T07:24:22","slug":"a-robot-that-senses-hidden-objects","status":"publish","type":"post","link":"https:\/\/www.revoscience.com\/en\/a-robot-that-senses-hidden-objects\/","title":{"rendered":"A robot that senses hidden objects"},"content":{"rendered":"\n

By Daniel Ackerman<\/strong> <\/p>\n\n\n\n

CAMBRIDGE, Mass (MIT News Office<\/em>)– In recent years, robots have gained artificial vision, touch, and even smell. \u201cResearchers have been giving robots human-like perception,\u201d says MIT Associate Professor Fadel Adib. In a new paper<\/a>, Adib\u2019s team is pushing the technology a step further. \u201cWe\u2019re trying to give robots superhuman perception,\u201d he says.<\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

The researchers have developed a robot that uses radio waves, which can pass through walls, to sense occluded objects. The robot, called RF-Grasp, combines this powerful sensing with more traditional computer vision to locate and grasp items that might otherwise be blocked from view. The advance could one day streamline e-commerce fulfillment in warehouses or help a machine pluck a screwdriver from a jumbled toolkit.<\/p>\n\n\n\n

The research will be presented in May at the IEEE International Conference on Robotics and Automation. The paper\u2019s lead author is Tara Boroushaki, a research assistant in the Signal Kinetics Group at the MIT Media Lab. Her MIT co-authors include Adib, who is the director of the Signal Kinetics Group; and Alberto Rodriguez, the Class of 1957 Associate Professor in the Department of Mechanical Engineering. Other co-authors include Junshan Leng, a research engineer at Harvard University, and Ian Clester, a PhD student at Georgia Tech.<\/p>\n\n\n\n

As e-commerce continues to grow, warehouse work is still usually the domain of humans, not robots, despite sometimes-dangerous working conditions. That\u2019s in part because robots struggle to locate and grasp objects in such a crowded environment. \u201cPerception and picking are two roadblocks in the industry today,\u201d says Rodriguez. Using optical vision alone, robots can\u2019t perceive the presence of an item packed away in a box or hidden behind another object on the shelf \u2014 visible light waves, of course, don\u2019t pass through walls.<\/p>\n\n\n\n

But radio waves can.<\/p>\n\n\n\n

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 \u2014 or, in the case of pets, implanted in \u2014 the item to be tracked. The reader then emits an RF signal, which gets modulated by the tag and reflected back to the reader.<\/p>\n\n\n\n

The reflected signal provides information about the location and identity of the tagged item. The technology has gained popularity in retail supply chains \u2014 Japan aims to use RF tracking for nearly all retail purchases<\/a> in a matter of years. The researchers realized this profusion of RF could be a boon for robots, giving them another mode of perception.<\/p>\n\n\n\n

\u201cRF is such a different sensing modality than vision,\u201d says Rodriguez. \u201cIt would be a mistake not to explore what RF can do.\u201d<\/p>\n\n\n\n

RF Grasp uses both a camera and an RF reader to find and grab tagged objects, even when they\u2019re fully blocked from the camera\u2019s view. It consists of a robotic arm attached to a grasping hand. The camera sits on the robot\u2019s wrist. The RF reader stands independent of the robot and relays tracking information to the robot\u2019s control algorithm. So, the robot is constantly collecting both RF tracking data and a visual picture of its surroundings. Integrating these two data streams into the robot\u2019s decision making was one of the biggest challenges the researchers faced.<\/p>\n\n\n\n

\u201cThe robot has to decide, at each point in time, which of these streams is more important to think about,\u201d says Boroushaki. \u201cIt\u2019s not just eye-hand coordination, it\u2019s RF-eye-hand coordination. So, the problem gets very complicated.\u201d<\/p>\n\n\n\n

The robot initiates the seek-and-pluck process by pinging the target object\u2019s RF tag for a sense of its whereabouts. \u201cIt starts by using RF to focus the attention of vision,\u201d says Adib. \u201cThen you use vision to navigate fine maneuvers.\u201d The sequence is akin to hearing a siren from behind, then turning to look and get a clearer picture of the siren\u2019s source.<\/p>\n\n\n\n

With its two complementary senses, RF Grasp zeroes in on the target object. As it gets closer and even starts manipulating the item, vision, which provides much finer detail than RF, dominates the robot\u2019s decision making.<\/p>\n\n\n\n

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. Plus, RF Grasp displayed the unique ability to \u201cdeclutter\u201d its environment \u2014 removing packing materials and other obstacles in its way in order to access the target. Rodriguez says this demonstrates RF Grasp\u2019s \u201cunfair advantage\u201d over robots without penetrative RF sensing. \u201cIt has this guidance that other systems simply don\u2019t have.\u201d<\/p>\n\n\n\n

RF Grasp could one day perform fulfillment in packed e-commerce warehouses. Its RF sensing could even instantly verify an item\u2019s identity without the need to manipulate the item, expose its barcode, then scan it. \u201cRF has the potential to improve some of those limitations in industry, especially in perception and localization,\u201d says Rodriguez.<\/p>\n\n\n\n

Adib also envisions potential home applications for the robot, like locating the right Allen wrench to assemble your Ikea chair. \u201cOr you could imagine the robot finding lost items. It\u2019s like a super-Roomba that goes and retrieves my keys, wherever the heck I put them.\u201d<\/p>\n\n\n\n

The research is sponsored by the National Science Foundation, NTT DATA, Toppan, Toppan Forms, and the Abdul Latif Jameel Water and Food Systems Lab (J-WAFS).<\/p>\n","protected":false},"excerpt":{"rendered":"

In recent years, robots have gained artificial vision, touch, and even smell. \u201cResearchers have been giving robots human-like perception,\u201d says MIT Associate Professor Fadel Adib.<\/p>\n","protected":false},"author":2,"featured_media":20321,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[3],"tags":[],"class_list":["post-20320","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news"],"featured_image_urls":{"full":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2021\/04\/MIT-RF-Grip-01-press.jpg",900,600,false],"thumbnail":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2021\/04\/MIT-RF-Grip-01-press-200x200.jpg",200,200,true],"medium":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2021\/04\/MIT-RF-Grip-01-press-600x400.jpg",600,400,true],"medium_large":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2021\/04\/MIT-RF-Grip-01-press-768x512.jpg",750,500,true],"large":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2021\/04\/MIT-RF-Grip-01-press-675x450.jpg",675,450,true],"1536x1536":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2021\/04\/MIT-RF-Grip-01-press.jpg",900,600,false],"2048x2048":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2021\/04\/MIT-RF-Grip-01-press.jpg",900,600,false],"ultp_layout_landscape_large":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2021\/04\/MIT-RF-Grip-01-press.jpg",900,600,false],"ultp_layout_landscape":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2021\/04\/MIT-RF-Grip-01-press.jpg",855,570,false],"ultp_layout_portrait":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2021\/04\/MIT-RF-Grip-01-press.jpg",600,400,false],"ultp_layout_square":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2021\/04\/MIT-RF-Grip-01-press.jpg",600,400,false],"newspaper-x-single-post":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2021\/04\/MIT-RF-Grip-01-press-760x490.jpg",760,490,true],"newspaper-x-recent-post-big":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2021\/04\/MIT-RF-Grip-01-press-550x360.jpg",550,360,true],"newspaper-x-recent-post-list-image":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2021\/04\/MIT-RF-Grip-01-press-95x65.jpg",95,65,true],"web-stories-poster-portrait":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2021\/04\/MIT-RF-Grip-01-press.jpg",640,427,false],"web-stories-publisher-logo":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2021\/04\/MIT-RF-Grip-01-press.jpg",96,64,false],"web-stories-thumbnail":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2021\/04\/MIT-RF-Grip-01-press.jpg",150,100,false]},"author_info":{"info":["RevoScience"]},"category_info":"News<\/a>","tag_info":"News","comment_count":"0","_links":{"self":[{"href":"https:\/\/www.revoscience.com\/en\/wp-json\/wp\/v2\/posts\/20320","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.revoscience.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.revoscience.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.revoscience.com\/en\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.revoscience.com\/en\/wp-json\/wp\/v2\/comments?post=20320"}],"version-history":[{"count":0,"href":"https:\/\/www.revoscience.com\/en\/wp-json\/wp\/v2\/posts\/20320\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.revoscience.com\/en\/wp-json\/wp\/v2\/media\/20321"}],"wp:attachment":[{"href":"https:\/\/www.revoscience.com\/en\/wp-json\/wp\/v2\/media?parent=20320"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.revoscience.com\/en\/wp-json\/wp\/v2\/categories?post=20320"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.revoscience.com\/en\/wp-json\/wp\/v2\/tags?post=20320"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}