全国政协副主席万钢当选中国科协第九届全委会主...
From Kiva Systems to PR2
“The Master created humans first as the lowest type, most easily formed. Gradually, he replaced them by robots, the next higher step, and finally he created me to take the place of the last humans.”
— Isaac Asimov, I, Robot
When people talk about Artificial Intelligence, they think of robots walking around. But in computer science, A.I. is the field focused on the development of the brain of not only such robots but of computers that want to achieve certain goals. These robots do not use any of the Deep Learning models that we talked about previously. Instead, they have encoded, handwritten software.
Boston Dynamics
In Florida, a competition between robots to reach a specific goal is watched by a few people to determine which one achieves the different objectives faster and more precisely. One robot looks at a door with its sensors — cameras, and lasers — to decide what to do next to open it. Using its robotic arm, it slowly pushes the door and goes to the other side. The team is responsible for the robot cheers as it completes one of the tasks.
This story might sound like science fiction or from a distant future, but the U.S. Defense Advanced Research Projects Agency (DARPA) organized that competition, the DARPA Robotics Challenge (DRC), in December 2013. Boston Dynamics created the robot that opened the door, Atlas, but many other robots attempted these tasks. And for each robot, the development teams that programmed them eagerly watched. The DRC’s goal was for robots to perform independent jobs inspired by situations dangerous to humans, like a nuclear power plant failure. The competition tested the robots’ agility, sensing, and manipulation capabilities. Upon first glance, the work seems pretty straightforward, like walking over terrain and opening doors, but they are difficult for robots to achieve. The most challenging assignment was to walk over an uneven surface because it is hard for robots to stay balanced. Most of the robots in the competition failed and did not complete many of the tasks because of a malfunction or the job was too hard. Atlas achieved the most.
DARPA program manager, Gill Pratt, said of the prototype, “A 1-year-old child can barely walk, a 1-year-old child falls down a lot, this is where we are right now.” Boston Dynamics revealed Atlas on July 11, 2013. At the first public appearance, the New York Times stated, “A striking example of how computers are beginning to grow legs and move around in the physical world,” describing the robot as “a giant — though shaky — step toward the long-anticipated age of humanoid robots.”
Boston Dynamics has the bold goal of making robots that are better than animals in mobility, dexterity, and perception. By building machines with dynamic movement and balance, their robots can go almost anywhere, on any terrain on Earth. They also want their robots to manipulate objects, hold them steady, and walk around without dropping them. And, they are approaching their goals as time progresses. Atlas continues to improve with lighter hardware, more capabilities, and improved software.
Atlas was much more advanced than the first robots from the 1960s like Stanford’s Shakey. But Boston Dynamics wanted to improve it, so they designed a second version — Atlas, The Next Generation. They first released a YouTube video of it in February 2016 where it walked on snow. Subsequent videos showed Atlas doing a backflip and jumping over a dog lying in the grass.
To build this updated version, Boston Dynamics used 3D printing to make parts of the robot look more like an animal. For example, its upper leg, which has hydraulic pathways, actuators, and filters, are all embedded and printed as one piece. That was not possible before 3D printing. They designed the structure using the knowledge of what the loads and behaviors of Atlas are, based on data from previous interactions of the original Atlas robots and its interaction with the environment. They also added software simulations. With the 3D-printing technique, Boston Dynamics transformed what was once a big, bulky, and slow robot weighing around 375 pounds into a much slimmer version at 165 pounds.
Boston Dynamics is not only focused on building humanoid robots, but it is also developing different looking cyborgs as well. They have two robotic dogs, Spot, and SpotMini. Like Atlas, the dogs can enter areas unsafe for humans in order to clear out space. Using cameras, the dogs look at the terrain, assesses the elevation of the floor, and figure out where they can step and what is necessary to climb to another region. These robotic machines continue to improve and are more agile and less clunky. The latest version dances to Bruno Mars’s hit song “Uptown Funk.” I believe this is only the beginning of the robotic revolution. Spot and other robots may end up in our everyday lives.
Kiva Systems
Giants like Amazon have been working on robots to increase their companies’ productivity. At an Amazon warehouse, small robots help Joe Cotler, a packer for the online retail giant. These automated machines cruise around the warehouse floor, delivering shelves full of items to humans, who then pick, pack, and ship the items without taking more than a couple of steps.
This automation is a considerable change for Amazon, where humans used to select and pack items themselves with only the help of conveyor belts and forklifts. With the introduction of robots by Kiva Systems, the Amazon warehouse processes completely changed. Now, humans stand in a set location, and robots move around the warehouse, alleviating most of the manual labor.
This change occurred when Amazon acquired Mick Mountz’s Kiva Systems for $775 million in 2012. After working years in business processes at Webvan, a now-defunct e-commerce startup, Mick realized that one of the reasons for the downfall was due to the high costs of order fulfillment. The company filed for bankruptcy in 2001 when the dot-com bubble exploded and later became part of Amazon. Mick found a better way to handle orders inside warehouses and started Kiva Systems with the help of robotics experts.
In a typical warehouse, humans fill orders by wandering through rows of shelves, often carrying portable radio-frequency scanners to locate products. Computer systems and conveyor belts sped things up but only to a point. With the help of robots, however, workers at Amazon process items three times faster and do not need to search for products. When an order comes into Amazon.com, a robot drives around a grid of shelves, locates the correct shelf, lifts it onto its back, and delivers it to a human worker. The person, then, completes the process by picking up the order, packing it, and then shipping it. Humans do not get much rest. To avoid human error, a red laser flashes on the item so that the human knows what to pick up. The robot, then, returns the shelf to the grid. As soon as the robot takes away the shelf, another one arrives so that the human is always working.
The Robot Operating System
To function, robots needed an operating system that could distill high-level instructions down to the hardware. This requirement is the same as for standard computers like communicating with the hard drive and display. Robots need to pass the information to its components, like arms, cameras, and wheels. In 2007, Scott Hansan, an early Google engineer who previously worked with Larry Page and Sergey Brin, started Willow Garage to advance robotics. The team developed the Robot Operating System (ROS) for its own robots, one of which was the Personal Robot 2 (PR2). Ultimately, they shared the open-source operating system with other companies.
The PR2 had two strong arms that performed delicate tasks like turning a page in a book. It contained pressure sensors in the arms as well as stereo cameras, a Light Detection and Ranging (LIDAR) sensor, an inertial measurement sensors. These sensors provided data for the robot to navigate in complex environments. Willow Garage developed ROS to understand the signals from these sensors as well as to control them.
ROS included a middle layer, which was communication between the software written by developers and the hardware, as well as software for object recognition and many other tasks. It provided a standard platform for programming different hardware and a growing array of packages that gave robots new capabilities. It included libraries and algorithms for vision, navigation, and manipulation among other things.
ROS enabled hobbyists and researchers to develop applications on top of hardware more easily. With ROS, robots play instruments, control high-flying acrobatic machines, walk, as well as fold laundry. Currently, ROS is under development by other hardware businesses like self-driving car companies. The newest version of the software, ROS 2.0, has many new capabilities, allowing, for example, the software to control multiple robots and allow for real-time control. As these systems improve, we may eventually have robots performing our house-cleaning chores.
