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关键词:机器人,机器人女仆,机械手臂,Microsoft Kinect照相机

来源:互联网    2015-11-17


May 30, 2012 04:54pm ETRobot Maid Cleans Up After Your Mess Robot Maid A robot places an item in a refrigerator. Credit: Saxena Lab View full size image

Robots could soon play maid and butler in homes, with a droid now programmed to scan a messy room, identify all items, figure out where they belong and put them back in place.

Such robots also could help pack warehouses and clean up auto repair shops, researchers say.

Previously scientists had developed robots that can grasp objects, but when it came to putting them back down again, the machines could place only single items down on flat surfaces. Now researchers are developing machines that can survey a group of things and place them in complex 3D spaces.

[Where's My Robot Maid?]

The robot, which has a single mechanical arm, surveys objects in rooms by using a Microsoft Kinect camera, which is equipped with an infrared scanner to help create 3D models of items. The Kinect was originally developed for video gaming but is being widely used by roboticists to help robots navigate rooms.

The droid weaves together many images to create an overall picture of a room. It then divides this view into blocks depending on their color and shape. The machine then computes how likely any block it sees is a given object. It then decides on an appropriate home for the item, creates a 3D model of the target space, and puts the object in that place, taking into account the shapes of both the item and the space for a stable placement.

(Before the exercise, the robot is shown examples of various kinds of items, such as books, to learn what characteristics they might have in common. The droid is also shown some examples of where to place objects beforehand, and from it learns where similar objects might or might not go, such as knowing not to put shoes in the refrigerator.)

The researchers' robot tidied up dishes, books, egg cartons, toys, clothing and other items — 98 objects in all — by placing them in 40 areas, such as bookshelves, dish racks, refrigerators, closets and on tables.

The robot proved up to 98 percent successful in recognizing and correctly putting away objects it had seen before.

"How can you possibly imagine that if a robot has neither seen a martini glass nor the stemware holder before, it would be able to put it away?" said researcher Ashutosh Saxena, a roboticist at Cornell University. "We show that it puts it away successfully — a hard task to do."

"It learned the common-sense physics principles of stability," Saxena told InnovationNewsDaily. "Learning these underlying principles from data allowed it to handle and adapt to new situations."

[Americans Willing to Pay for Laundry-Folding Robots]

The robot was also capable of placing objects it had never seen before, but success rates fell to an average of 82 percent. Objects that were most often misidentified had ambiguous shapes — for instance, clothing and shoes. In addition, "perceiving whether a beer bottle is full or empty is hard, and therefore it has never quite figured out what to do with beer bottles — it just throws all of them into the recycling bin, empty or full, for now," Saxena said.

The world already has vacuum cleaner robots, with more than 8 million Roombas sold, and "very soon, I think two to four years, we'll see more capable robots — for example, a 2-foot-tall robot with a small arm that not only vacuums the floor, but also picks up and places things on the side," Saxena said. He noted his team will soon have such mobile robots that they can program with their algorithms.

Still, "this work is only a first step towards a cleaning and house-arranging robot," Saxena said. "A lot needs to be done before this robot could be useful. Would you be happy if it breaks one out of five glasses? No. What about one in 50? Maybe. Breaking only one in 5,000 would be really awesome. However, it takes a lot to go from 1 in 50, where we are now, to breaking only 1 in 5,000."

The researchers hope to improve the robot with higher-resolution cameras. Tactile sensors in the droid's hand also could help it know whether an object is in a stable position and can be released.

The machine also could be programmed to understand the preferences in which objects should belong — for instance, the TV remote control ideally would go next to the sofa in front of the TV.

Saxena and his colleagues detailed their findings online in the May issue of the International Journal of Robotics.

This story was provided by InnovationNewsDaily, a sister site to LiveScience. Follow InnovationNewsDaily on Twitter @News_Innovation, or on Facebook.



Robot女仆清理后你Mess Robot Maid机器人在冰箱中放置一个项目。




[哪里是我的机器人女仆?Where's My Robot Maid?微软Kinect摄像头,配备了一个红外扫描仪,以帮助创建项目的3D模型。 Kinect的最初是为视频游戏,但正在被广泛使用的机器人专家来帮助机器人导航室.



研究人员的机器人收拾餐具,书籍,蛋盒,玩具,服装等物品— 98物体在所有的—通过将它们在40个地区,如书架,菜架,冰箱,衣柜和桌子上.


u0026 QUOT以前见过的对象,你怎么能这样可能想像,如果一个机器人既没有看到一个马提尼酒杯,也没有之前的高脚杯持有人,这将是能够把它扔掉&QUOT?;研究人员说,Ashutosh说Saxena先生,一个机器人专家在康奈尔大学。 "我们发现,它把它扔掉成功—一个硬任务来完成"。

"学到稳定的常识性的物理学原理," Saxena先生告诉InnovationNewsDaily。 "从数据中学习这些基本原则,允许它来处理,并适应新的形势和QUOT;

[美国人愿意支付洗衣,折叠机器人Americans Willing to Pay for Laundry-Folding Robots成功率下降到平均82%。对象是最经常误了暧昧的形状—例如,衣服和鞋子。此外,"感知一个啤酒瓶是否满或空是很难的,因此它从来没有完全想通了,做什么用啤酒瓶—它只是抛出所有的人都变成了回收站,空或满,就目前而言," Saxena先生说.

世界上已经有吸尘器机器人,拥有超过800万Roombas销售,并与QUOT;很快,我觉得两到四年,我们将看到更强大的机器人—例如,一个2英尺高的机器人用小臂,不仅吸尘地板上,而且拾取并放置东西的一侧," Saxena先生说。他指出,他的团队很快就会有这样的移动机器人,他们可以用自己的算法编程.

但是,"这项工作是迈向清洁和房子安排机器人,&QUOT只是第一步; Saxena先生说。 "需要大量的工作要做在此之前的机器人可能是有用的。你会很高兴,如果它打破了五分之一的眼镜?什么号大约每50?有可能。打破只有5000人会真正真棒。然而,这需要大量的从1到去50,我们现在的情况,仅1 5000突破和QUOT;