Tag Archives: mobile
#437600 Brain-Inspired Robot Controller Uses ...
Robots operating in the real world are starting to find themselves constrained by the amount of computing power they have available. Computers are certainly getting faster and more efficient, but they’re not keeping up with the potential of robotic systems, which have access to better sensors and more data, which in turn makes decision making more complex. A relatively new kind of computing device called a memristor could potentially help robotics smash through this barrier, through a combination of lower complexity, lower cost, and higher speed.
In a paper published today in Science Robotics, a team of researchers from the University of Southern California in Los Angeles and the Air Force Research Laboratory in Rome, N.Y., demonstrate a simple self-balancing robot that uses memristors to form a highly effective analog control system, inspired by the functional structure of the human brain.
First, we should go over just what the heck a memristor is. As the name suggests, it’s a type of memory that is resistance-based. That is, the resistance of a memristor can be programmed, and the memristor remembers that resistance even after it’s powered off (the resistance depends on the magnitude of the voltage applied to the memristor’s two terminals and the length of time that voltage has been applied). Memristors are potentially the ideal hybrid between RAM and flash memory, offering high speed, high density, non-volatile storage. So that’s cool, but what we’re most interested in as far as robot control systems go is that memristors store resistance, making them analog devices rather than digital ones.
By adding a memristor to an analog circuit with inputs from a gyroscope and an accelerometer, the researchers created a completely analog Kalman filter, which coupled to a second memristor functioned as a PD controller.
Nowadays, the word “analog” sounds like a bad thing, but robots are stuck in an analog world, and any physical interactions they have with the world (mediated through sensors) are fundamentally analog in nature. The challenge is that an analog signal is often “messy”—full of noise and non-linearities—and as such, the usual approach now is to get it converted to a digital signal and then processed to get anything useful out of it. This is fine, but it’s also not particularly fast or efficient. Where memristors come in is that they’re inherently analog, and in addition to storing data, they can also act as tiny analog computers, which is pretty wild.
By adding a memristor to an analog circuit with inputs from a gyroscope and an accelerometer, the researchers, led by Wei Wu, an associate professor of electrical engineering at USC, created a completely analog and completely physical Kalman filter to remove noise from the sensor signal. In addition, they used a second memristor can be used to turn that sensor data into a proportional-derivative (PD) controller. Next they put those two components together to build an analogy system that can do a bunch of the work required to keep an inverted pendulum robot upright far more efficiently than a traditional system. The difference in performance is readily apparent:
The shaking you see in the traditionally-controlled robot on the bottom comes from the non-linearity of the dynamic system, which changes faster than the on-board controller can keep up with. The memristors substantially reduce the cycle time, so the robot can balance much more smoothly. Specifically, cycle time is reduced from 3,034 microseconds to just 6 microseconds.
Of course, there’s more going on here, like motor drivers and a digital computer to talk to them, so this robot is really a hybrid system. But guess what? As the researchers point out, so are we!
The human brain consists of the cerebrum, the cerebellum, and the brainstem. The cerebrum is a major part of the brain in charge of vision, hearing, and thinking, whereas the cerebellum plays an important role in motion control. Through this cooperation of the cerebrum and the cerebellum, the human brain can conduct multiple tasks simultaneously with extremely low power consumption. Inspired by this, we developed a hybrid analog-digital computation platform, in which the digital component runs the high-level algorithm, whereas the analog component is responsible for sensor fusion and motion control.
By offloading a bunch of computation onto the memristors, the higher brain functions of the robot have more breathing room. Overall, you reduce power, space, and cost, while substantially improving performance. This has only become possible relatively recently due to memristor advances and availability, and the researchers expect that memristor-based hybrid computing will soon be able to “improve the robustness and the performance of mobile robotic systems with higher” degrees of freedom.
“A memristor-based hybrid analog-digital computing platform for mobile robotics,” by Buyun Chen, Hao Yang, Boxiang Song, Deming Meng, Xiaodong Yan, Yuanrui Li, Yunxiang Wang, Pan Hu, Tse-Hsien Ou, Mark Barnell, Qing Wu, Han Wang, and Wei Wu, from USC Viterbi and AFRL, was published in Science Robotics. Continue reading →
Posted in Human Robots
#437598 Video Friday: Sarcos Is Developing a New ...
Video Friday is your weekly selection of awesome robotics videos, collected by your Automaton bloggers. We’ll also be posting a weekly calendar of upcoming robotics events for the next few months; here's what we have so far (send us your events!):
IROS 2020 – October 25-29, 2020 – [Online]
ROS World 2020 – November 12, 2020 – [Online]
CYBATHLON 2020 – November 13-14, 2020 – [Online]
ICSR 2020 – November 14-16, 2020 – Golden, Colo., USA
Let us know if you have suggestions for next week, and enjoy today's videos.
NASA’s Origins, Spectral Interpretation, Resource Identification, Security, Regolith Explorer (OSIRIS-REx) spacecraft unfurled its robotic arm Oct. 20, 2020, and in a first for the agency, briefly touched an asteroid to collect dust and pebbles from the surface for delivery to Earth in 2023.
[ NASA ]
New from David Zarrouk’s lab at BGU is AmphiSTAR, which Zarrouk describes as “a kind of a ground-water drone inspired by the cockroaches (sprawling) and by the Basilisk lizard (running over water). The robot hovers due to the collision of its propellers with the water (hydrodynamics not aerodynamics). The robot can crawl and swim at high and low speeds and smoothly transition between the two. It can reach 3.5 m/s on ground and 1.5m/s in water.”
AmphiSTAR will be presented at IROS, starting next week!
[ BGU ]
This is unfortunately not a great video of a video that was taken at a SoftBank Hawks baseball game in Japan last week, but it’s showing an Atlas robot doing an honestly kind of impressive dance routine to support the team.
ロボット応援団に人型ロボット『ATLAS』がアメリカからリモートで緊急参戦！！！
ホークスビジョンの映像をお楽しみ下さい♪#sbhawks #Pepper #spot pic.twitter.com/6aTYn8GGli
— 福岡ソフトバンクホークス（公式） (@HAWKS_official)
October 16, 2020
Editor’s Note: The tweet embed above is not working for some reason—see the video here.
[ SoftBank Hawks ]
Thanks Thomas!
Sarcos is working on a new robot, which looks to be the torso of their powered exoskeleton with the human relocated somewhere else.
[ Sarcos ]
The biggest holiday of the year, International Sloth Day, was on Tuesday! To celebrate, here’s Slothbot!
[ NSF ]
This is one of those simple-seeming tasks that are really difficult for robots.
I love self-resetting training environments.
[ MIT CSAIL ]
The Chiel lab collaborates with engineers at the Center for Biologically Inspired Robotics Research at Case Western Reserve University to design novel worm-like robots that have potential applications in search-and-rescue missions, endoscopic medicine, or other scenarios requiring navigation through narrow spaces.
[ Case Western ]
ANYbotics partnered with Losinger Marazzi to explore ANYmal’s potential of patrolling construction sites to identify and report safety issues. With such a complex environment, only a robot designed to navigate difficult terrain is able to bring digitalization to such a physically demanding industry.
[ ANYbotics ]
Happy 2018 Halloween from Clearpath Robotics!
[ Clearpath ]
Overcoming illumination variance is a critical factor in vision-based navigation. Existing methods tackled this radical illumination variance issue by proposing camera control or high dynamic range (HDR) image fusion. Despite these efforts, we have found that the vision-based approaches still suffer from overcoming darkness. This paper presents real-time image synthesizing from carefully controlled seed low dynamic range (LDR) image, to enable visual simultaneous localization and mapping (SLAM) in an extremely dark environment (less than 10 lux).
[ KAIST ]
What can MoveIt do? Who knows! Let's find out!
[ MoveIt ]
Thanks Dave!
Here we pick a cube from a starting point, manipulate it within the hand, and then put it back. To explore the capabilities of the hand, no sensors were used in this demonstration. The RBO Hand 3 uses soft pneumatic actuators made of silicone. The softness imparts considerable robustness against variations in object pose and size. This lets us design manipulation funnels that work reliably without needing sensor feedback. We take advantage of this reliability to chain these funnels into more complex multi-step manipulation plans.
[ TU Berlin ]
If this was a real solar array, King Louie would have totally cleaned it. Mostly.
[ BYU ]
Autonomous exploration is a fundamental problem for various applications of unmanned aerial vehicles(UAVs). Existing methods, however, were demonstrated to have low efficiency, due to the lack of optimality consideration, conservative motion plans and low decision frequencies. In this paper, we propose FUEL, a hierarchical framework that can support Fast UAV ExpLoration in complex unknown environments.
[ HKUST ]
Countless precise repetitions? This is the perfect task for a robot, thought researchers at the University of Liverpool in the Department of Chemistry, and without further ado they developed an automation solution that can carry out and monitor research tasks, making autonomous decisions about what to do next.
[ Kuka ]
This video shows a demonstration of central results of the SecondHands project. In the context of maintenance and repair tasks, in warehouse environments, the collaborative humanoid robot ARMAR-6 demonstrates a number of cognitive and sensorimotor abilities such as 1) recognition of the need of help based on speech, force, haptics and visual scene and action interpretation, 2) collaborative bimanual manipulation of large objects, 3) compliant mobile manipulation, 4) grasping known and unknown objects and tools, 5) human-robot interaction (object and tool handover) 6) natural dialog and 7) force predictive control.
[ SecondHands ]
In celebration of Ada Lovelace Day, Silicon Valley Robotics hosted a panel of Women in Robotics.
[ Robohub ]
As part of the upcoming virtual IROS conference, HEBI robotics is putting together a tutorial on robotics actuation. While I’m sure HEBI would like you to take a long look at their own actuators, we’ve been assured that no matter what kind of actuators you use, this tutorial will still be informative and useful.
[ YouTube ] via [ HEBI Robotics ]
Thanks Dave!
This week’s UMD Lockheed Martin Robotics Seminar comes from Julie Shah at MIT, on “Enhancing Human Capability with Intelligent Machine Teammates.”
Every team has top performers- people who excel at working in a team to find the right solutions in complex, difficult situations. These top performers include nurses who run hospital floors, emergency response teams, air traffic controllers, and factory line supervisors. While they may outperform the most sophisticated optimization and scheduling algorithms, they cannot often tell us how they do it. Similarly, even when a machine can do the job better than most of us, it can’t explain how. In this talk I share recent work investigating effective ways to blend the unique decision-making strengths of humans and machines. I discuss the development of computational models that enable machines to efficiently infer the mental state of human teammates and thereby collaborate with people in richer, more flexible ways.
[ UMD ]
Matthew Piccoli gives a talk to the UPenn GRASP Lab on “Trading Complexities: Smart Motors and Dumb Vehicles.”
We will discuss my research journey through Penn making the world's smallest, simplest flying vehicles, and in parallel making the most complex brushless motors. What do they have in common? We'll touch on why the quadrotor went from an obscure type of helicopter to the current ubiquitous drone. Finally, we'll get into my life after Penn and what tools I'm creating to further drone and robot designs of the future.
[ UPenn ] Continue reading →
Posted in Human Robots
#437579 Disney Research Makes Robotic Gaze ...
While it’s not totally clear to what extent human-like robots are better than conventional robots for most applications, one area I’m personally comfortable with them is entertainment. The folks over at Disney Research, who are all about entertainment, have been working on this sort of thing for a very long time, and some of their animatronic attractions are actually quite impressive.
The next step for Disney is to make its animatronic figures, which currently feature scripted behaviors, to perform in an interactive manner with visitors. The challenge is that this is where you start to get into potential Uncanny Valley territory, which is what happens when you try to create “the illusion of life,” which is what Disney (they explicitly say) is trying to do.
In a paper presented at IROS this month, a team from Disney Research, Caltech, University of Illinois at Urbana-Champaign, and Walt Disney Imagineering is trying to nail that illusion of life with a single, and perhaps most important, social cue: eye gaze.
Before you watch this video, keep in mind that you’re watching a specific character, as Disney describes:
The robot character plays an elderly man reading a book, perhaps in a library or on a park bench. He has difficulty hearing and his eyesight is in decline. Even so, he is constantly distracted from reading by people passing by or coming up to greet him. Most times, he glances at people moving quickly in the distance, but as people encroach into his personal space, he will stare with disapproval for the interruption, or provide those that are familiar to him with friendly acknowledgment.
What, exactly, does “lifelike” mean in the context of robotic gaze? The paper abstract describes the goal as “[seeking] to create an interaction which demonstrates the illusion of life.” I suppose you could think of it like a sort of old-fashioned Turing test focused on gaze: If the gaze of this robot cannot be distinguished from the gaze of a human, then victory, that’s lifelike. And critically, we’re talking about mutual gaze here—not just a robot gazing off into the distance, but you looking deep into the eyes of this robot and it looking right back at you just like a human would. Or, just like some humans would.
The approach that Disney is using is more animation-y than biology-y or psychology-y. In other words, they’re not trying to figure out what’s going on in our brains to make our eyes move the way that they do when we’re looking at other people and basing their control system on that, but instead, Disney just wants it to look right. This “visual appeal” approach is totally fine, and there’s been an enormous amount of human-robot interaction (HRI) research behind it already, albeit usually with less explicitly human-like platforms. And speaking of human-like platforms, the hardware is a “custom Walt Disney Imagineering Audio-Animatronics bust,” which has DoFs that include neck, eyes, eyelids, and eyebrows.
In order to decide on gaze motions, the system first identifies a person to target with its attention using an RGB-D camera. If more than one person is visible, the system calculates a curiosity score for each, currently simplified to be based on how much motion it sees. Depending on which person that the robot can see has the highest curiosity score, the system will choose from a variety of high level gaze behavior states, including:
Read: The Read state can be considered the “default” state of the character. When not executing another state, the robot character will return to the Read state. Here, the character will appear to read a book located at torso level.
Glance: A transition to the Glance state from the Read or Engage states occurs when the attention engine indicates that there is a stimuli with a curiosity score […] above a certain threshold.
Engage: The Engage state occurs when the attention engine indicates that there is a stimuli […] to meet a threshold and can be triggered from both Read and Glance states. This state causes the robot to gaze at the person-of-interest with both the eyes and head.
Acknowledge: The Acknowledge state is triggered from either Engage or Glance states when the person-of-interest is deemed to be familiar to the robot.
Running underneath these higher level behavior states are lower level motion behaviors like breathing, small head movements, eye blinking, and saccades (the quick eye movements that occur when people, or robots, look between two different focal points). The term for this hierarchical behavioral state layering is a subsumption architecture, which goes all the way back to Rodney Brooks’ work on robots like Genghis in the 1980s and Cog and Kismet in the ’90s, and it provides a way for more complex behaviors to emerge from a set of simple, decentralized low-level behaviors.
“25 years on Disney is using my subsumption architecture for humanoid eye control, better and smoother now than our 1995 implementations on Cog and Kismet.”
—Rodney Brooks, MIT emeritus professor
Brooks, an emeritus professor at MIT and, most recently, cofounder and CTO of Robust.ai, tweeted about the Disney project, saying: “People underestimate how long it takes to get from academic paper to real world robotics. 25 years on Disney is using my subsumption architecture for humanoid eye control, better and smoother now than our 1995 implementations on Cog and Kismet.”
From the paper:
Although originally intended for control of mobile robots, we find that the subsumption architecture, as presented in [17], lends itself as a framework for organizing animatronic behaviors. This is due to the analogous use of subsumption in human behavior: human psychomotor behavior can be intuitively modeled as layered behaviors with incoming sensory inputs, where higher behavioral levels are able to subsume lower behaviors. At the lowest level, we have involuntary movements such as heartbeats, breathing and blinking. However, higher behavioral responses can take over and control lower level behaviors, e.g., fight-or-flight response can induce faster heart rate and breathing. As our robot character is modeled after human morphology, mimicking biological behaviors through the use of a bottom-up approach is straightforward.
The result, as the video shows, appears to be quite good, although it’s hard to tell how it would all come together if the robot had more of, you know, a face. But it seems like you don’t necessarily need to have a lifelike humanoid robot to take advantage of this architecture in an HRI context—any robot that wants to make a gaze-based connection with a human could benefit from doing it in a more human-like way.
“Realistic and Interactive Robot Gaze,” by Matthew K.X.J. Pan, Sungjoon Choi, James Kennedy, Kyna McIntosh, Daniel Campos Zamora, Gunter Niemeyer, Joohyung Kim, Alexis Wieland, and David Christensen from Disney Research, California Institute of Technology, University of Illinois at Urbana-Champaign, and Walt Disney Imagineering, was presented at IROS 2020. You can find the full paper, along with a 13-minute video presentation, on the IROS on-demand conference website.
< Back to IEEE Journal Watch Continue reading →
Posted in Human Robots
#437571 Video Friday: Snugglebot Is What We All ...
Video Friday is your weekly selection of awesome robotics videos, collected by your Automaton bloggers. We’ll also be posting a weekly calendar of upcoming robotics events for the next few months; here's what we have so far (send us your events!):
IROS 2020 – October 25-25, 2020 – [Online]
Robotica 2020 – November 10-14, 2020 – [Online]
ROS World 2020 – November 12, 2020 – [Online]
CYBATHLON 2020 – November 13-14, 2020 – [Online]
ICSR 2020 – November 14-16, 2020 – Golden, Colo., USA
Bay Area Robotics Symposium – November 20, 2020 – [Online]
Let us know if you have suggestions for next week, and enjoy today's videos.
Snugglebot is what we all need right now.
[ Snugglebot ]
In his video message on his prayer intention for November, Pope Francis emphasizes that progress in robotics and artificial intelligence (AI) be oriented “towards respecting the dignity of the person and of Creation”.
[ Vatican News ]
KaPOW!
Apparently it's supposed to do that—the disruptor flies off backwards to reduce recoil on the robot, and has its own parachute to keep it from going too far.
[ Ghost Robotics ]
Animals have many muscles, receptors, and neurons which compose feedback loops. In this study, we designed artificial muscles, receptors, and neurons without any microprocessors, or software-based controllers. We imitate the reflexive rule observed in walking experiments of cats, as a result, the Pneumatic Brainless Robot II emerged running motion (a leg trajectory and a gait pattern) through the interaction between the body, the ground, and the artificial reflexes. We envision that the simple reflex circuit we discovered will be a candidate for a minimal model for describing the principles of animal locomotion.
Find the paper, “Brainless Running: A Quasi-quadruped Robot with Decentralized Spinal Reflexes by Solely Mechanical Devices,” on IROS On-Demand.
[ IROS ]
Thanks Yoichi!
I have no idea what these guys are saying, but they're talking about robots that serve chocolate!
The world of experience of the Zotter Schokoladen Manufaktur of managing director Josef Zotter counts more than 270,000 visitors annually. Since March 2019, this world of chocolate in Bergl near Riegersburg in Austria has been enriched by a new attraction: the world's first chocolate and praline robot from KUKA delights young and old alike and serves up chocolate and pralines to guests according to their personal taste.
[ Zotter ]
This paper proposes a systematic solution that uses an unmanned aerial vehicle (UAV) to aggressively and safely track an agile target. The solution properly handles the challenging situations where the intent of the target and the dense environments are unknown to the UAV. The proposed solution is integrated into an onboard quadrotor system. We fully test the system in challenging real-world tracking missions. Moreover, benchmark comparisons validate that the proposed method surpasses the cutting-edge methods on time efficiency and tracking effectiveness.
[ FAST Lab ]
Southwest Research Institute developed a cable management system for collaborative robotics, or “cobots.” Dress packs used on cobots can create problems when cables are too tight (e-stops) or loose (tangling). SwRI developed ADDRESS, or the Adaptive DRESing System, to provide smarter cobot dress packs that address e-stops and tangling.
[ SWRI ]
A quick demonstration of the acoustic contact sensor in the RBO Hand 2. An embedded microphone records the sound inside of the pneumatic finger. Depending on which part of the finger makes contact, the sound is a little bit different. We create a sensor that recognizes these small changes and predicts the contact location from the sound. The visualization on the left shows the recorded sound (top) and which of the nine contact classes the sensor is currently predicting (bottom).
[ TU Berlin ]
The MAVLab won the prize for the “most innovative design” in the IMAV 2018 indoor competition, in which drones had to fly through windows, gates, and follow a predetermined flight path. The prize was awarded for the demonstration of a fully autonomous version of the “DelFly Nimble”, a tailless flapping wing drone.
In order to fly by itself, the DelFly Nimble was equipped with a single, small camera and a small processor allowing onboard vision processing and control. The jury of international experts in the field praised the agility and autonomous flight capabilities of the DelFly Nimble.
[ MAVLab ]
A reactive walking controller for the Open Dynamic Robot Initiative's skinny quadruped.
[ ODRI ]
Mobile service robots are already able to recognize people and objects while navigating autonomously through their operating environments. But what is the ideal position of the robot to interact with a user? To solve this problem, Fraunhofer IPA developed an approach that connects navigation, 3D environment modeling, and person detection to find the optimal goal pose for HRI.
[ Fraunhofer ]
Yaskawa has been in robotics for a very, very long time.
[ Yaskawa ]
Black in Robotics IROS launch event, featuring Carlotta Berry.
[ Black in Robotics ]
What is AI? I have no idea! But these folks have some opinions.
[ MIT ]
Aerial-based Observations of Volcanic Emissions (ABOVE) is an international collaborative project that is changing the way we sample volcanic gas emissions. Harnessing recent advances in drone technology, unoccupied aerial systems (UAS) in the ABOVE fleet are able to acquire aerial measurements of volcanic gases directly from within previously inaccessible volcanic plumes. In May 2019, a team of 30 researchers undertook an ambitious field deployment to two volcanoes – Tavurvur (Rabaul) and Manam in Papua New Guinea – both amongst the most prodigious emitters of sulphur dioxide on Earth, and yet lacking any measurements of how much carbon they emit to the atmosphere.
[ ABOVE ]
A talk from IHMC's Robert Griffin for ICCAS 2020, including a few updates on their Nadia humanoid.
[ IHMC ] Continue reading →
Posted in Human Robots
#437550 McDonald’s Is Making a Plant-Based ...
Fast-food chains have been doing what they can in recent years to health-ify their menus. For better or worse, burgers, fries, fried chicken, roast beef sandwiches, and the like will never go out of style—this is America, after all—but consumers are increasingly gravitating towards healthier options.
One of those options is plant-based foods, and not just salads and veggie burgers, but “meat” made from plants. Burger King was one of the first big fast-food chains to jump on the plant-based meat bandwagon, introducing its Impossible Whopper in restaurants across the country last year after a successful pilot program. Dunkin’ (formerly Dunkin’ Donuts) uses plant-based patties in its Beyond Sausage breakfast sandwiches.
But there’s one big player in the fast food market that’s been oddly missing from the plant-based trend—until now. McDonald’s announced last week that it will debut a sandwich called the McPlant in key US markets next year. Unlike Dunkin’ and Burger King, who both worked with Impossible Foods to make their plant-based products, McDonald’s worked with Los Angeles-based Beyond Meat, which makes chicken, beef, and pork-like products from plants.
According to Bloomberg, though, McDonald’s decided to forego a partnership with Beyond Meat in favor of creating its own plant-based products. Imitation chicken nuggets and plant-based breakfast sandwiches are in its plans as well.
McDonald’s has bounced back impressively from its March low (when the coronavirus lockdowns first happened in the US). Last month the company’s stock reached a 52-week high of $231 per share (as compared to its low in March of $124 per share).
To keep those numbers high and make it as easy as possible for customers to get their hands on plant-based burgers and all the traditional menu items too, the fast food chain is investing in tech and integrating more digital offerings into its restaurants.
McDonald’s has acquired a couple artificial intelligence companies in the last year and a half; Dynamic Yield is an Israeli company that uses AI to personalize customers’ experiences, and McDonald’s is using Dynamic Yield’s tech on its smart menu boards, for example by customizing the items displayed on the drive-thru menu based on the weather and the time of day, and recommending additional items based on what a customer asks for first (i.e. “You know what would go great with that coffee? Some pancakes!”).
The fast food giant also bought Apprente, a startup that uses AI in voice-based ordering platforms. McDonald’s is using the tech to help automate its drive-throughs.
In addition to these investments, the company plans to launch a digital hub called MyMcDonald’s that will include a loyalty program, start doing deliveries of its food through its mobile app, and test different ways of streamlining the food order and pickup process—with many of the new ideas geared towards pandemic times, like express pickup lanes for people who placed digital orders and restaurants with drive-throughs for delivery and pickup orders only.
Plant-based meat patties appear to be just one small piece of McDonald’s modernization plans. Those of us who were wondering what they were waiting for should have known—one of the most-recognized fast food chains in the world wasn’t about to let itself get phased out. It seems it will only be a matter of time until you can pull out your phone, make a few selections, and have a burger made from plants—with a side of fries made from more plants—show up at your door a little while later. Drive-throughs, shouting your order into a fuzzy speaker with a confused teen on the other end, and burgers made from beef? So 2019.
Image Credit: McDonald’s Continue reading →
Posted in Human Robots