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The WIRED Guide to Robots

Modern robots are not unlike toddlers: It’s hilarious to watch them fall over, but deep down we know that if we laugh too hard, they might develop a complex and grow up to start World War III. None of humanity’s creations inspires such a confusing mix of awe, admiration, and fear: We want robots to make our lives easier and safer, yet we can’t quite bring ourselves to trust them. We’re crafting them in our own image, yet we are terrified they’ll supplant us.

But that trepidation is no obstacle to the booming field of robotics. Robots have finally grown smart enough and physically capable enough to make their way out of factories and labs to walk and roll and even leap among us . The machines have arrived.

You may be worried a robot is going to steal your job, and we get that. This is capitalism, after all, and automation is inevitable. But you may be more likely to work alongside a robot in the near future than have one replace you. And even better news: You’re more likely to make friends with a robot than have one murder you. Hooray for the future!

The Complete History And Future of Robots

The definition of “robot” has been confusing from the very beginning. The word first appeared in 1921, in Karel Capek’s play R.U.R. , or Rossum's Universal Robots. “Robot” comes from the Czech for “forced labor.” These robots were robots more in spirit than form, though. They looked like humans, and instead of being made of metal, they were made of chemical batter. The robots were far more efficient than their human counterparts, and also way more murder-y—they ended up going on a killing spree .

R.U.R. would establish the trope of the Not-to-Be-Trusted Machine (e.g., Terminator , The Stepford Wives , Blade Runner , etc.) that continues to this day—which is not to say pop culture hasn’t embraced friendlier robots. Think Rosie from The Jetsons . (Ornery, sure, but certainly not homicidal.) And it doesn’t get much family-friendlier than Robin Williams as Bicentennial Man .

The real-world definition of “robot” is just as slippery as those fictional depictions. Ask 10 roboticists and you’ll get 10 answers—how autonomous does it need to be, for instance. But they do agree on some general guidelines : A robot is an intelligent, physically embodied machine. A robot can perform tasks autonomously to some degree. And a robot can sense and manipulate its environment.

Think of a simple drone that you pilot around. That’s no robot. But give a drone the power to take off and land on its own and sense objects and suddenly it’s a lot more robot-ish. It’s the intelligence and sensing and autonomy that’s key.

But it wasn’t until the 1960s that a company built something that started meeting those guidelines. That’s when SRI International in Silicon Valley developed Shakey , the first truly mobile and perceptive robot. This tower on wheels was well-named—awkward, slow, twitchy. Equipped with a camera and bump sensors, Shakey could navigate a complex environment. It wasn’t a particularly confident-looking machine, but it was the beginning of the robotic revolution.

Around the time Shakey was trembling about, robot arms were beginning to transform manufacturing. The first among them was Unimate , which welded auto bodies. Today, its descendants rule car factories, performing tedious, dangerous tasks with far more precision and speed than any human could muster. Even though they’re stuck in place, they still very much fit our definition of a robot—they’re intelligent machines that sense and manipulate their environment.

Robots, though, remained largely confined to factories and labs, where they either rolled about or were stuck in place lifting objects. Then, in the mid-1980s Honda started up a humanoid robotics program. It developed P3, which could walk pretty darn good and also wave and shake hands, much to the delight of a roomful of suits . The work would culminate in Asimo, the famed biped, which once tried to take out President Obama with a well-kicked soccer ball. (OK, perhaps it was more innocent than that.)

Today, advanced robots are popping up everywhere . For that you can thank three technologies in particular: sensors, actuators, and AI.

So, sensors. Machines that roll on sidewalks to deliver falafel can only navigate our world thanks in large part to the 2004 Darpa Grand Challenge, in which teams of roboticists cobbled together self-driving cars to race through the desert. Their secret? Lidar, which shoots out lasers to build a 3-D map of the world. The ensuing private-sector race to develop self-driving cars has dramatically driven down the price of lidar, to the point that engineers can create perceptive robots on the (relative) cheap.

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Lidar is often combined with something called machine vision—2-D or 3-D cameras that allow the robot to build an even better picture of its world. You know how Facebook automatically recognizes your mug and tags you in pictures? Same principle with robots. Fancy algorithms allow them to pick out certain landmarks or objects .

Sensors are what keep robots from smashing into things. They’re why a robot mule of sorts can keep an eye on you, following you and schlepping your stuff around ; machine vision also allows robots to scan cherry trees to determine where best to shake them , helping fill massive labor gaps in agriculture.

New technologies promise to let robots sense the world in ways that are far beyond humans’ capabilities. We’re talking about seeing around corners: At MIT, researchers have developed a system that watches the floor at the corner of, say, a hallway, and picks out subtle movements being reflected from the other side that the piddling human eye can’t see. Such technology could one day ensure that robots don’t crash into humans in labyrinthine buildings, and even allow self-driving cars to see occluded scenes.

Within each of these robots is the next secret ingredient: the actuator , which is a fancy word for the combo electric motor and gearbox that you’ll find in a robot’s joint. It’s this actuator that determines how strong a robot is and how smoothly or not smoothly it moves . Without actuators, robots would crumple like rag dolls. Even relatively simple robots like Roombas owe their existence to actuators. Self-driving cars, too, are loaded with the things.

Actuators are great for powering massive robot arms on a car assembly line, but a newish field, known as soft robotics, is devoted to creating actuators that operate on a whole new level. Unlike mule robots, soft robots are generally squishy, and use air or oil to get themselves moving. So for instance, one particular kind of robot muscle uses electrodes to squeeze a pouch of oil, expanding and contracting to tug on weights . Unlike with bulky traditional actuators, you could stack a bunch of these to magnify the strength: A robot named Kengoro, for instance, moves with 116 actuators that tug on cables, allowing the machine to do unsettlingly human maneuvers like pushups . It’s a far more natural-looking form of movement than what you’d get with traditional electric motors housed in the joints.

And then there’s Boston Dynamics, which created the Atlas humanoid robot for the Darpa Robotics Challenge in 2013. At first, university robotics research teams struggled to get the machine to tackle the basic tasks of the original 2013 challenge and the finals round in 2015, like turning valves and opening doors. But Boston Dynamics has since that time turned Atlas into a marvel that can do backflips , far outpacing other bipeds that still have a hard time walking. (Unlike the Terminator, though, it does not pack heat.) Boston Dynamics has also begun leasing a quadruped robot called Spot, which can recover in unsettling fashion when humans kick or tug on it . That kind of stability will be key if we want to build a world where we don’t spend all our time helping robots out of jams. And it’s all thanks to the humble actuator.

At the same time that robots like Atlas and Spot are getting more physically robust, they’re getting smarter, thanks to AI. Robotics seems to be reaching an inflection point, where processing power and artificial intelligence are combining to truly ensmarten the machines . And for the machines, just as in humans, the senses and intelligence are inseparable—if you pick up a fake apple and don’t realize it’s plastic before shoving it in your mouth, you’re not very smart.

This is a fascinating frontier in robotics (replicating the sense of touch, not eating fake apples). A company called SynTouch, for instance, has developed robotic fingertips that can detect a range of sensations , from temperature to coarseness. Another robot fingertip from Columbia University replicates touch with light, so in a sense it sees touch : It’s embedded with 32 photodiodes and 30 LEDs, overlaid with a skin of silicone. When that skin is deformed, the photodiodes detect how light from the LEDs changes to pinpoint where exactly you touched the fingertip, and how hard.

Far from the hulking dullards that lift car doors on automotive assembly lines, the robots of tomorrow will be very sensitive indeed.

The Complete History And Future of Robots

Increasingly sophisticated machines may populate our world, but for robots to be really useful, they’ll have to become more self-sufficient. After all, it would be impossible to program a home robot with the instructions for gripping each and every object it ever might encounter. You want it to learn on its own, and that is where advances in artificial intelligence come in.

Take Brett. In a UC Berkeley lab, the humanoid robot has taught itself to conquer one of those children’s puzzles where you cram pegs into different shaped holes. It did so by trial and error through a process called reinforcement learning. No one told it how to get a square peg into a square hole, just that it needed to. So by making random movements and getting a digital reward (basically, yes, do that kind of thing again ) each time it got closer to success, Brett learned something new on its own . The process is super slow, sure, but with time roboticists will hone the machines’ ability to teach themselves novel skills in novel environments, which is pivotal if we don’t want to get stuck babysitting them.

Another tack here is to have a digital version of a robot train first in simulation, then port what it has learned to the physical robot in a lab. Over at Google , researchers used motion-capture videos of dogs to program a simulated dog, then used reinforcement learning to get a simulated four-legged robot to teach itself to make the same movements. That is, even though both have four legs, the robot’s body is mechanically distinct from a dog’s, so they move in distinct ways. But after many random movements, the simulated robot got enough rewards to match the simulated dog. Then the researchers transferred that knowledge to the real robot in the lab, and sure enough, the thing could walk—in fact, it walked even faster than the robot manufacturer’s default gait, though in fairness it was less stable.

13 Robots, Real and Imagined

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They may be getting smarter day by day, but for the near future we are going to have to babysit the robots. As advanced as they’ve become, they still struggle to navigate our world. They plunge into fountains , for instance. So the solution, at least for the short term, is to set up call centers where robots can phone humans to help them out in a pinch . For example, Tug the hospital robot can call for help if it’s roaming the halls at night and there’s no human around to move a cart blocking its path. The operator would them teleoperate the robot around the obstruction.

Speaking of hospital robots. When the coronavirus crisis took hold in early 2020, a group of roboticists saw an opportunity: Robots are the perfect coworkers in a pandemic. Engineers must use the crisis, they argued in an editorial , to supercharge the development of medical robots, which never get sick and can do the dull, dirty, and dangerous work that puts human medical workers in harm’s way. Robot helpers could take patients’ temperatures and deliver drugs, for instance. This would free up human doctors and nurses to do what they do best: problem-solving and being empathetic with patients, skills that robots may never be able to replicate.

The rapidly developing relationship between humans and robots is so complex that it has spawned its own field, known as human-robot interaction . The overarching challenge is this: It’s easy enough to adapt robots to get along with humans—make them soft and give them a sense of touch—but it’s another issue entirely to train humans to get along with the machines. With Tug the hospital robot, for example, doctors and nurses learn to treat it like a grandparent—get the hell out of its way and help it get unstuck if you have to. We also have to manage our expectations: Robots like Atlas may seem advanced, but they’re far from the autonomous wonders you might think.

What humanity has done is essentially invented a new species, and now we’re maybe having a little buyers’ remorse. Namely, what if the robots steal all our jobs? Not even white-collar workers are safe from hyper-intelligent AI, after all.

A lot of smart people are thinking about the singularity, when the machines grow advanced enough to make humanity obsolete. That will result in a massive societal realignment and species-wide existential crisis. What will we do if we no longer have to work? How does income inequality look anything other than exponentially more dire as industries replace people with machines?

These seem like far-out problems, but now is the time to start pondering them. Which you might consider an upside to the killer-robot narrative that Hollywood has fed us all these years: The machines may be limited at the moment, but we as a society need to think seriously about how much power we want to cede. Take San Francisco, for instance, which is exploring the idea of a robot tax, which would force companies to pay up when they displace human workers.

I can’t sit here and promise you that the robots won’t one day turn us all into batteries , but the more realistic scenario is that, unlike in the world of R.U.R. , humans and robots are poised to live in harmony—because it’s already happening. This is the idea of multiplicity , that you’re more likely to work alongside a robot than be replaced by one. If your car has adaptive cruise control, you’re already doing this, letting the robot handle the boring highway work while you take over for the complexity of city driving. The fact that the US economy ground to a standstill during the coronavirus pandemic made it abundantly clear that robots are nowhere near ready to replace humans en masse.

The machines promise to change virtually every aspect of human life, from health care to transportation to work. Should they help us drive? Absolutely. (They will, though, have to make the decision to sometimes kill , but the benefits of precision driving far outweigh the risks.) Should they replace nurses and cops? Maybe not—certain jobs may always require a human touch.

One thing is abundantly clear: The machines have arrived. Now we have to figure out how to handle the responsibility of having invented a whole new species.

The Complete History And Future of Robots

If You Want a Robot to Learn Better, Be a Jerk to It A good way to make a robot learn is to do the work in simulation, so the machine doesn’t accidentally hurt itself. Even better, you can give it tough love by trying to knock objects out of its hand.

Spot the Robot Dog Trots Into the Big, Bad World Boston Dynamics' creation is starting to sniff out its role in the workforce: as a helpful canine that still sometimes needs you to hold its paw.

Finally, a Robot That Moves Kind of Like a Tongue Octopus arms and elephant trunks and human tongues move in a fascinating way, which has now inspired a fascinating new kind of robot.

Robots Are Fueling the Quiet Ascendance of the Electric Motor For something born over a century ago, the electric motor really hasn’t fully extended its wings. The problem? Fossil fuels are just too easy, and for the time being, cheap. But now, it’s actually robots, with their actuators, that are fueling the secret ascendence of the electric motor.

This Robot Fish Powers Itself With Fake Blood A robot lionfish uses a rudimentary vasculature and “blood” to both energize itself and hydraulically power its fins.

Inside the Amazon Warehouse Where Humans and Machines Become One In an Amazon sorting center, a swarm of robots works alongside humans. Here’s what that says about Amazon—and the future of work.

This guide was last updated on April 13, 2020.

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FREE K-12 standards-aligned STEM

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Find more at TeachEngineering.org .

  • TeachEngineering
  • What Is a Robot?

Lesson What Is a Robot?

Grade Level: 5 (4-7)

Time Required: 45 minutes

Lesson Dependency: None

Subject Areas: Science and Technology

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Curriculum in this Unit Units serve as guides to a particular content or subject area. Nested under units are lessons (in purple) and hands-on activities (in blue). Note that not all lessons and activities will exist under a unit, and instead may exist as "standalone" curriculum.

  • Understanding Communication with a Robot
  • NXT Ball Shooter
  • Understanding Movement in Humans and Robots
  • Movement Task Using Sensors - Humans and Robots

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Engineering connection, learning objectives, worksheets and attachments, introduction/motivation, associated activities, lesson closure, additional multimedia support, user comments & tips.

Engineers help design and create healthier tomorrows

Engineers have used robots to create many technologies that students see every day, a number of which are shown in the lesson's PowerPoint presentation. In the activity, students are asked to design a program to solve a problem as if they are engineers. To conclude, students are asked to think creatively about ways they could use robots to solve problems. Through this lesson and activity, students build a basic understanding of robotics through looking at how engineers have used them.

After this lesson, students should be able to:

  • Define what a robot is.
  • Describe the main components of a robot.
  • Explain how the LEGO MINDSTORMS EV3 robot can be programmed to move.
  • Explain how engineers apply robotics to solve real-world problems.

Educational Standards Each TeachEngineering lesson or activity is correlated to one or more K-12 science, technology, engineering or math (STEM) educational standards. All 100,000+ K-12 STEM standards covered in TeachEngineering are collected, maintained and packaged by the Achievement Standards Network (ASN) , a project of D2L (www.achievementstandards.org). In the ASN, standards are hierarchically structured: first by source; e.g. , by state; within source by type; e.g. , science or mathematics; within type by subtype, then by grade, etc .

Ngss: next generation science standards - science, international technology and engineering educators association - technology.

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Missouri - science.

The What Is a Robot? Presentation PowerPoint file provides the content material for this lesson. Refer to the text in the Lesson Background section to for how to introduce the material, slide by slide.

The lesson PowerPoint presentation provides great examples and is designed to provide a basic introduction to robotics prior to programming the LEGO MINDSTORMS EV3 systems. This lesson also introduces the basic characteristics found in all robots, including sensors, inputs, processing and outputs, using the LEGO robot as an example.

To bring it all together, the associate activity introduces the concept of how precise commands to a robot need to be in order to make sure the robot does exactly what is expected of it.

Lesson Background and Concepts for Teachers

Use the What Is a Robot? Presentation (PowerPoint slides) to teach the lesson. Another set of PowerPoint slides that is attached to the associated activity, " Activity: Understanding Communications with a Robot ," is for the second day of this combined lesson and activity. Use the guidance below for what to expect in each slide and how to use it to teach the lesson and activity. In advance, make copies of the pre/post assessment sheets.

What is a Robot? (Slides 1-16 of Lesson Presentation)

  • Tell the students: What is a robot? Today we will be talking about robots and learning how to work with robots.
  • Hand out copies of the pre-assessment sheet (slide 2). Give students five minutes to fill them out. The answers are on slide 3.
  • Use slides 4-5 to clear popular culture-driven misconceptions about what robots are and what they do. Then, define what a robot is using slide 6. Emphasize how engineers have used robots to make our lives easier with the examples given in the slide including automatic doors, industrial robots, and automatic car washes. Depending on time, show a couple of videos from those listed on slide 7.
  • Introduce the LEGO EV3 with slide 8 and let students know that the name of the particular robot that they will be working with is called the "taskbot," which is shown on the slide.
  • Introduce the first main component of robots, the computer, using slides 9-10. Before moving on, make sure students understand that when you refer to a computer, you are not talking about a desktop computer! Instead, you are talking about a small computer chip, such as is found in anything with a digital screen (digital clock, digital thermostat, digital microwave, etc.) as well as in cars, video game consoles, and even inside a desktop computer! The chip inside a desktop "computer" is actually the real computer. This is also known as the processor.
  • With slide 11, introduce the computer "intelligent brick" of the LEGO EV3 robot. The main purpose of this slide is to get them familiar with the term "EV3 computer brick."
  • WIth slide 12, introduce the second important component of a robot: inputs. Continue with the example of a desktop computer, this time talking about the mouse and keyboard as inputs.
  • With slide 13, introduce the inputs of the EV3. The EV3 has four input ports at the bottom of the computer brick. A variety of sensors can be used as inputs to the EV3 brick. The standard EV3 kit comes with a touch sensor, a color sensor, an ultrasonic sensor and a rotation sensor. Additional and more advanced sensors are also available.
  • With slide 14, introduce the third component of a robot: outputs. Use a personal computer monitor as another example. Again, make sure students understand that the actual computer is a small chip that sends output to the monitor. Another example is a robot motor. The computer chip of a robot sends its output to the motors of the robot.
  • Looking at slide 15, talk about the outputs of the  computer brick. The output ports are located at the top of the brick and they send output signals to motors or the EV3 lamp.
  • Slide 16 is a summary of the lesson content. Review the basic components of robots to make sure students have a grasp of the material before conducting the associated activity.
  • Understanding Communication with a Robot - Student teams act out robot instructions and then program a LEGO EV3 taskbot to go through a simple maze. Through the human and robot examples, students see that a robot's computer simply follows instructions as given, thus one must be logical and precise with programming instruction. They also see how robot sensors are used to perform movement tasks.

(Use this closure at lesson end or after completion of the associated activity. The goal is to verify that students understand the three main robot components: computer, inputs and outputs. Use a real-world engineering example to ask students to think about these components, such as the example below, an automatic door at a grocery store.)

An automatic door at a grocery store is an everyday example of a robot that engineers have designed to make our lives easier. What are some ways the automatic door makes peoples' lives easier? (Possible answers: A person carrying many bags does not have to put down the bags to open the door. More people can go through the door more quickly. A person in a wheelchair can enter/exit more easily. An employee can push in a long line of carts without having to hold the door.)

What are three things that an automatic door would need to have in order to be a robot? (Answer: Output, computer and input.)

Let's see if it has those three things. What is the output of the automatic door? (Answer: A motor makes the door open.)

What does the computer do? (Answer: It takes in an input that tells it a person is approaching the door, and when it receives this input, it opens the door.)

Now, I want you to think like an engineer. Let's look at the sensors we have with the EV3 robot and think about how we could use each one to sense a person approaching the door so the computer knows to open it.

Touch sensor : How might you use a touch sensor to let the computer know a person is approaching the door? (Answer: You could put a touch sensor on the ground to walk on. Or make a wall button like the handicap buttons often placed on nearby walls.)]

Color sensor : How would you use a color sensor? (Answer: You could direct a beam of light across the path to the door pointed at the sensor. When somebody walks through the beam, the color sensor would sense that the beam was broken and open the door.)

Ultrasonic sensor : What does the ultrasonic sensor do? (Answer: It sends out high-frequency sounds that you cannot hear and senses when they reflect back from objects. In this way, it can tell the distance to an object.) How might you use an ultrasonic sensor to let you know when someone is approaching the door? (Answer: Point the sensor in front of the door and when a person approaches, the distance to the nearest object would be the distance to that person. When that person is a specified distance from the door, the computer could sense it and open the door.)

(Note: The provided answers are just possible ways that the EV3 sensors could be used in automatic doors, and students may come up with other solutions that would work. Encourage them to think creatively about the challenge. You might also ask them what problems they see with these solutions. This is the way engineers would approach this challenge, looking for a wide range of possible solutions and eventually deciding on the best solution for a given situation.)

Pre-Lesson Assessment

Before beginning the lesson, administer the three-question Pre-Lesson Assessment Sheet (also slide 2). Answers are provided in slide 3.

Post-Lesson Assessment

After conducting the associated activity, administer the three-question Post-Lesson Assessment Sheet (same as the pre-lesson assessment) to make sure that students understand what a robot is and how detailed they must be in writing robot instructions. Compare pre/post answers to assess student progress.

  • LEGO Robots (Quicktime video)
  • Engineering for the Red Planet (Quicktime video)
  • Anatomy of a Rover (Flash interactive)
  • Kismet (Quicktime video)
  • RoboSnail (Quicktime video)
  • Robofly (QuickTime Video)
  • Design Inspired by Nature (Flash image)

What Is a Robot? Teachers' Domain. Accessed 11/9/2010. (overview and examples) http://www.teachersdomain.org/resource/eng06.sci.engin.design.lp_robot/

Robotics: Thinking, Sensing and Acting. The Tech Museum of Innovation. Accessed 7/10/2013. http://www.thetech.org/learning-resources/robotics

Contributors

Supporting program, acknowledgements.

This curriculum was developed under National Science Foundation GK-12 grant no. DGE 0440524. However, these contents do not necessarily represent the policies of the National Science Foundation, and you should not assume endorsement by the federal government.

Last modified: February 8, 2019

Robotics: What Are Robots? Robotics Definition & Uses.

presentation of robots

Robotics Technology

Robotics is an interdisciplinary sector of science and engineering dedicated to the design, construction and use of mechanical robots. Our guide will give you a concrete grasp of robotics, including different types of robots and how they’re being applied across industries.

industrial robots on assembly line

What Is Robotics?

Robotics is the intersection of science, engineering and technology that produces machines, called robots, that replicate or substitute for human actions. Robots perform basic and repetitive tasks with greater efficiency and accuracy than humans, making them ideal for industries like manufacturing. However, the introduction of artificial intelligence in robotics has given robots the ability to handle increasingly complex situations in various industries.

What Is a Robot?

A robot is a programmable machine that can complete a task, while the term robotics describes the field of study focused on developing robots and automation. Each robot has a different level of autonomy. These levels range from human-controlled bots that carry out tasks to fully-autonomous bots that perform tasks without any external influences.

In terms of etymology, the word ‘robot’ is derived from the Czech word robota , which means “forced labor.” The word first appeared in the 1920 play R.U.R. , in reference to the play’s characters who were mass-produced workers incapable of creative thinking.

Robotics Aspects

Mechanical construction.

The mechanical aspect of a robot helps it complete tasks in the environment for which it’s designed. For example, the Mars 2020 Rover’s wheels are individually motorized and made of titanium tubing that help it firmly grip the harsh terrain of the red planet.

Electrical Components

Robots need electrical components that control and power the machinery. Essentially, an electric current — a battery, for example — is needed to power a large majority of robots.

Software Program

Robots contain at least some level of computer programming. Without a set of code telling it what to do, a robot would just be another piece of simple machinery. Inserting a program into a robot gives it the ability to know when and how to carry out a task.

What Are the Main Components of a Robot?

Control system.

Computation includes all of the components that make up a robot’s central processing unit, often referred to as its control system. Control systems are programmed to tell a robot how to utilize its specific components, similar in some ways to how the human brain sends signals throughout the body, in order to complete a specific task. These robotic tasks could comprise anything from minimally invasive surgery to assembly line packing.

Sensors provide a robot with stimuli in the form of electrical signals that are processed by the controller and allow the robot to interact with the outside world. Common sensors found within robots include video cameras that function as eyes, photoresistors that react to light and microphones that operate like ears. These sensors allow the robot to capture its surroundings and process the most logical conclusion based on the current moment and allows the controller to relay commands to the additional components.

A device can only be considered to be a robot if it has a movable frame or body. Actuators are the components that are responsible for this movement. These components are made up of motors that receive signals from the control system and move in tandem to carry out the movement necessary to complete the assigned task. Actuators can be made of a variety of materials, such as metal or elastic, and are commonly operated by use of compressed air (pneumatic actuators) or oil (hydraulic actuators) but come in a variety of formats to best fulfill their specialized roles.

Power Supply

Like the human body requires food in order to function, robots require power. Stationary robots, such as those found in a factory, may run on AC power through a wall outlet but more commonly, robots operate via an internal battery. Most robots utilize lead-acid batteries for their safe qualities and long shelf life while others may utilize the more compact but also more expensive silver-cadmium variety. Safety, weight, replaceability and lifecycle are all important factors to consider when designing a robot’s power supply. 

Some potential power sources for future robotic development also include pneumatic power from compressed gasses, solar power, hydraulic power, flywheel energy storage organic garbage through anaerobic digestion and nuclear power.

End Effectors

End effectors are the physical, typically external components that allow robots to finish carrying out their tasks. Robots in factories often have interchangeable tools like paint sprayers and drills, surgical robots may be equipped with scalpels and other kinds of robots can be built with gripping claws or even hands for tasks like deliveries, packing, bomb diffusion and much more.

How Do Robots Work?

Some robots are pre-programmed to perform specific functions, meaning they operate in a controlled environment where they do simple, monotonous tasks — like a mechanical arm on an automotive assembly line.

Other robots are autonomous, operating independently of human operators to carry out tasks in open environments. In order to work, they use sensors to perceive the world around them, and then employ decision-making structures (usually a computer) to take the optimal next step based on their data and mission.

Robots may also work by using wireless networks to enable human control from a safe distance. These teleoperated robots usually work in extreme geographical conditions, weather and circumstances. Examples of teleoperated robots are the human-controlled submarines used to fix underwater pipe leaks during the BP oil spill or drones used to detect landmines on a battlefield.

Types of Robotics

Humanoid robots.

Humanoid robots are robots that look like or mimic human behavior. These robots usually perform human-like activities (like running, jumping and carrying objects), and are sometimes designed to look like us, even having human faces and expressions. Two of the most prominent examples of humanoid robots are Hanson Robotics’ Sophia and Boston Dynamics’ Atlas .

Cobots , or collaborative robots, are robots designed to work alongside humans. These robots prioritize safety by using sensors to remain aware of their surroundings, executing slow movements and ceasing actions when their movements are obstructed. Cobots typically perform simple tasks, freeing up humans to address more complex work.

Industrial Robots

Industrial robots automate processes in manufacturing environments like factories and warehouses. Possessing at least one robotic arm, these robots are made to handle heavy objects while moving with speed and precision. As a result, industrial robots often work in assembly lines to boost productivity.

Medical Robots

Medical robots assist healthcare professionals in various scenarios and support the physical and mental health of humans. These robots rely on AI and sensors to navigate healthcare facilities, interact with humans and execute precise movements. Some medical robots can even converse with humans, encouraging people’s social and emotional growth.

Agricultural Robots

Agricultural robots handle repetitive and labor-intensive tasks, allowing farmers to use their time and energy more efficiently. These robots also operate in greenhouses, where they monitor crops and help with harvests. Agricultural robots come in many forms, ranging from autonomous tractors to drones that collect data for farmers to analyze.

Microrobotics

Microrobotics is the study and development of robots on a miniature scale. Often no bigger than a millimeter, microrobots can vary in size, depending on the situation. Biotech researchers typically use microrobotics to monitor and treat diseases, with the goal of improving diagnostic tools and creating more targeted solutions.

Augmenting Robots

Augmenting robots, also known as VR robots , either enhance current human capabilities or replace the capabilities a human may have lost. The field of robotics for human augmentation is a field where science fiction could become reality very soon, with bots that have the ability to redefine the definition of humanity by making humans faster and stronger. Some examples of current augmenting robots are robotic prosthetic limbs or exoskeletons used to lift hefty weights.

Software Bots

Software bots, or simply ‘bots,’ are computer programs which carry out tasks autonomously. They are not technically considered robots. One common use case of software robots is a chatbot , which is a computer program that simulates conversation both online and over the phone and is often used in customer service scenarios. Chatbots can either be simple services that answer questions with an automated response or more complex digital assistants that learn from user information.

Robotics Applications

Beginning as a major boon for manufacturers, robotics has become a mainstay technology for a growing number of industries.

Manufacturing

Industrial robots can assemble products, sort items, perform welds and paint objects. They may even be used to fix and maintain other machines in a factory or warehouse. 

Medical robots transport medical supplies, perform surgical procedures and offer emotional support to those going through rehabilitation.  

Companionship

Social robots can support children with learning disabilities and act as a therapeutic tool for people with dementia. They also have business applications like providing in-person customer service in hotels and moving products around warehouses. 

Consumers may be most familiar with the Roomba and other robot vacuum cleaners. However, other home robots include lawn-mowing robots and personal robot assistants that can play music, engage with children and help with household chores.

Search and Rescue

Search and rescue robots can save those stuck in flood waters, deliver supplies to those stranded in remote areas and put out fires when conditions become too extreme for firefighters.

Pros and Cons of Robotics

Robotics comes with a number of benefits and drawbacks.

Pros of Robotics

  • Increased accuracy. Robots can perform movements and actions with greater precision and accuracy than humans.
  • Enhanced productivity. Robots can work at a faster pace than humans and don’t get tired, leading to more consistent and higher-volume production. 
  • Improved safety. Robots can take on tasks and operate in environments unsafe for humans, protecting workers from injuries. 
  • Rapid innovation. Many robots are equipped with sensors and cameras that collect data, so teams can quickly refine processes. 
  • Greater cost-efficiency. Gains in productivity may make robots a more cost-efficient option for businesses compared to hiring more human workers.

Cons of Robotics

  • Job losses. Robotic process automation may put human employees out of work, especially those who don’t have the skills to adapt to a changing workplace.  
  • Limited creativity. Robots may not react well to unexpected situations since they don’t have the same problem-solving skills as humans. 
  • Data security risks. Robots can be hit with cyber attacks, potentially exposing large amounts of data if they’re connected to the Internet of Things.  
  • Maintenance costs. Robots can be expensive to repair and maintain, and faulty equipment can lead to disruptions in production and revenue losses.  
  • Environmental waste. Extracting raw materials to build robots and having to discard disposable parts can lead to more environmental waste and pollution.

humanoid robot

Future of Robotics

The evolution of AI has major implications for the future of robotics. In factories, AI can be combined with robotics to produce digital twins and design simulations to help companies improve their workflows. Advanced AI also gives robots increased autonomy. For example, drones could deliver packages to customers without any human intervention. In addition, robots could be outfitted with generative AI tools like ChatGPT, resulting in more complex human-robot conversations.

As robots’ intelligence has shifted, so too have their appearances. Humanoid robots are designed to visually appeal to humans in various settings while understanding and responding to emotions, carrying objects and navigating environments. With these forms and abilities, robots can become major contributors in customer service, manufacturing, logistics and healthcare, among other industries.

While the spread of robotics has stoked fears over job losses due to automation, robots could simply change the nature of human jobs. Humans may find themselves collaborating with robots, letting their robotic counterparts handle repetitive tasks while they focus on more difficult problems. Either way, humans will need to adapt to the presence of robots as robotics continues to progress alongside other technologies like AI and deep learning.  

old robot

History of Robotics

Robotics as a concept goes back to ancient times. The ancient Greeks combined automation and engineering to create the Antikythera, a handheld device that predicted eclipses. Centuries later, Leonardo Da Vinci designed a mechanical knight now known as “Leonardo’s Robot.” But it was the rise of manufacturing during the Industrial Revolution that highlighted the need for widespread automation.

Following William Grey Walter’s development of the first autonomous robots in 1948, George Devol created the first industrial robotic arm known as Unimate. It began operating at a GM facility in 1959. In 1972, the Stanford Research Institute designed Shakey — the first AI-powered robot. Shakey used cameras and sensors to collect data from its surroundings and inform its next moves.

The ability of robots to perceive their surroundings led researchers to explore whether they could also perceive human emotions. In the late 1990s, MIT’s Dr. Cynthia Breazeal built Kismet, a robotic head that used facial features to express and respond to human emotions. This predecessor to social robots opened the door for future robots like Roomba and consumer-centric inventions like Alexa and other voice assistants.

Robots took another leap forward in 2012 due to a breakthrough in deep learning. Armed with volumes of digital images, British AI expert Geoffrey Hinton and his team successfully trained a system of neural networks to sort over one million images while making few errors. Since then, companies have incorporated deep learning into their technologies, promising more possibilities for robotics.

1700s (1737) Jacques de Vaucanson builds the first biomechanical automaton on record. Called the Flute Player, the mechanical device plays 12 songs.

1920s (1920) The word “robot” makes its first appearance in Karel Capek’s play R.U.R. Robot is derived from the Czech word “robota,” which means “forced labor.”

1930s (1936) Alan Turing publishes “On Computable Numbers,” a paper that introduces the concept of a theoretical computer called the Turing Machine.

1940s (1948) Cybernetics or Control and Communication in the Animal is published by MIT professor Norbert Wiener. The book speaks on the concept of communications and control in electronic, mechanical and biological systems.

(1949) William Grey Walter, a neurophysiologist and inventor, introduces Elmer and Elsie, a pair of battery-operated robots that look like tortoises. The robots move objects, find a source of light and find their way back to a charging station.

1950s (1950) Isaac Asimov publishes the Three Laws of Robotics .

(1950) Alan Turing publishes the paper “Computing Machinery and Intelligence,” proposing what is now known as the Turing Test, a method for determining if a machine is intelligent.

1960s (1961) The first robotic arm works in a General Motors facility. The arm lifts and stacks metal parts and follows a program for approximately 200 movements. The arm was created by George Devol and his partner Joseph Engelberger.

(1969) Victor Scheinman invents the Stanford Arm, a robotic arm with six joints that can mimic the movements of a human arm. It is one of the first robots designed to be controlled by a computer.

1970s (1972) A group of engineers at the Stanford Research Institute create Shakey, the first robot to use artificial intelligence.

(1978) Hiroshi Makino, an automation researcher, designs a four-axis SCARA robotic arm.

1980s (1985) The first documented use of a robot-assisted surgical procedure uses the PUMA 560 robotic surgical arm.

(1985) William Whittaker builds two remotely-operated robots that are sent to the Three Mile Island nuclear power plant.

(1989) MIT researchers Rodney Brooks and A. M. Flynn publish  Fast, Cheap and Out of Control: A Robot Invasion of the Solar System .

(1997) Sojourner lands on Mars. The free-ranging rover sends 2.3 billion bits of data back to Earth.

(1998) Furby, a robotic toy pet developed by Tiger Electronics, is released and eventually sells tens of millions of units. Furbys are preprogrammed to speak gibberish and learn other languages over time. 

(1999) Aibo, a robotic puppy powered by AI hits the commercial market. Developed by Sony, the robotic dog reacts to sounds and has some pre-programmed behavior.

2000s (2000) Cynthia Breazeal creates a robotic head, called Kismet, programmed to provoke emotions as well as react to them.

(2002) iRobot creates Roomba. The vacuum robot is the first robot to become popular in the commercial sector amongst the public. 

(2003) Mick Mountz and the cofounders of Amazon Robotics (formerly Kiva Systems) invent the Kiva robot. The robot maneuvers around warehouses and moves goods.

(2004) Boston Dynamics unveils BigDog, a quadruped robot controlled by humans.

(2004) The Defense Department’s Defense Advanced Research Projects Agency establishes the DARPA Grand Challenge. A self-driving car race that aims to inspire innovation in military autonomous vehicle tech.

2010s (2011) NASA and General Motors collaborate to send Robonaut 2, a humanesque robotic assistant, into space on space shuttle Discovery. The robot becomes a permanent resident of the International Space Station.

(2013) Boston Dynamics releases Atlas, a humanoid biped robot that uses 28 hydraulic joints to mimic human movements — including performing a backflip.

(2012) The first license for a self-driven car is issued in Nevada. The car is a Toyota Prius modified with technology developed by Google. 

(2016) Sophia, a humanoid robot dubbed the first robot citizen, is created by Hanson Robotics. The robot is capable of facial recognition, verbal communication and facial expression.

2020s (2020) Robots are used to distribute Covid-19 tests and vaccinations. 

(2020) 384,000 industrial robots are shipped across the globe to perform various manufacturing and warehouse jobs.  

(2021) Cruise, an autonomous car company, conducts its first two robotaxi test rides in San Francisco.

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introduction to robotics

INTRODUCTION TO ROBOTICS

Nov 19, 2014

1.95k likes | 3.66k Views

INTRODUCTION TO ROBOTICS. Presentation Objectives. Definition Types of Robot History Timeline Laws of Robotics Components Uses. Body Effectors Actuators Sensors Controller Software. Definition.

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Presentation Transcript

INTRODUCTION TOROBOTICS

Presentation Objectives • Definition • Types of Robot • History • Timeline • Laws of Robotics • Components • Uses • Body • Effectors • Actuators • Sensors • Controller • Software

Definition • “A re-programmable, multi-functional manipulator designed to move material, parts, tools, or specialized devices through various programmed motions for the performance of a variety of tasks” - Robot Institute of America, 1979 • “An automatic device that performs functions normally ascribed to humans or a machine in the form of a human.” - Webster's Dictionary

Types of Robot • Simple Level Robots • Middle Level Robots • Complex Level Robots • Are automatic machines that extend human potential. • Do work that humans can but should not do. • Are programmable, multipurpose, electromechanical machines. • Do work that humans normally do. • Are reprogrammable, multifunctional, manipulators. • Are designed to move materials, tools and parts through programmed paths. • Are suited for a variety of tasks.

History • Leonardo da Vinci (1452–1519) sketched plans for a humanoid robot around 1495. Da Vinci's notebooks, rediscovered in the 1950s, contain detailed drawings of a mechanical knight now known as Leonardo's robot, able to sit up, wave its arms and move its head and jaw. • In 1738 and 1739, Jacques De Vaucanson exhibited several life-sized automatons: a flute player, a pipe player and a duck. The mechanical duck could flap its wings, crane its neck, and swallow food from the exhibitor's hand, and it gave the illusion of digesting its food by excreting matter stored in a hidden compartment. Complex mechanical toys and animals built in Japan in the 1700s were described in the Karakuri zui (Illustrated Machinery, 1796). (Tea-serving karakuri, with mechanism, 19th century. Tokyo National Science Museum.)

History • The first industrial robot: UNIMATE • 1954: The first programmable robot is designed by George Devol, who coins the term Universal Automation. He later shortens this to Unimation, which becomes the name of the first robot company (1962). UNIMATE originally automated the manufacture of TV picture tubes

History • 1978: The Puma (Programmable Universal Machine for Assembly) robot is developed by Unimation with a General Motors design support. PUMA 560 Manipulator

History • 1980s: The robot industry enters a phase of rapid growth. Many institutions introduce programs and courses in robotics. Robotics courses are spread across mechanical engineering, electrical engineering, and computer science departments. Adept's SCARA robots Cognex In-Sight Robot Barrett Technology Manipulator

History • 1995 - present: Emerging applications in small robotics and mobile robots drive a second growth of start-up companies and research 2003: NASA’s Mars Exploration Rovers will launch toward Mars in search of answers about the history of water on Mars

1206 First programmable humanoid robots Boat with four robotic musicians Al-Jazari Timeline • Date: • Significance: • Robot Name: • Inventor:

1206 1495 First programmable humanoid robots Designs for a humanoid robot Boat with four robotic musicians Mechanical knight Al-Jazari Leonardo Da Vinci Timeline • Date: • Significance: • Robot Name: • Inventor:

1495 1738 Designs for a humanoid robot Mechanical duck that was able to eat, flap its wings, and excrete Mechanical knight Digesting Duck Leonardo Da Vinci Jacques de Vaucanson Timeline • Date: • Significance: • Robot Name: • Inventor:

1738 1800s Mechanical duck that was able to eat, flap its wings, and excrete Japanese mechanical toys that served tea, fired arrows, and painted Digesting Duck Karakuri toys Jacques de Vaucanson Hisashige Tanaka Timeline • Date: • Significance: • Robot Name: • Inventor:

1800s 1921 Japanese mechanical toys that served tea, fired arrows, and painted First fictional automata called "robots" appear in the play R.U.R. Karakuri toys Rossum's Universal Robots Hisashige Tanaka Karel Čapek Timeline • Date: • Significance: • Robot Name: • Inventor:

1921 1930s First fictional automata called "robots" appear in the play R.U.R. Humanoid robot exhibited at the 1939 and 1940 World's Fairs Rossum's Universal Robots Elektro Karel Čapek Westinghouse Electric Corporation Timeline • Date: • Significance: • Robot Name: • Inventor:

1930s 1948 Humanoid robot exhibited at the 1939 and 1940 World's Fairs Simple robots exhibiting biological behaviors Elektro Elsie and Elmer Westinghouse Electric Corporation William Grey Walter Timeline • Date: • Significance: • Robot Name: • Inventor:

1948 1956 First commercial robot, from the Unimation company founded by George Devol and Joseph Engelberger, based on Devol's patents Simple robots exhibiting biological behaviors Elsie and Elmer Unimate William Grey Walter George Devol Timeline • Date: • Significance: • Robot Name: • Inventor:

1956 1961 First commercial robot, from the Unimation company founded by George Devol and Joseph Engelberger, based on Devol's patents First installed industrial robot Unimate Unimate George Devol George Devol Timeline • Date: • Significance: • Robot Name: • Inventor:

1961 1963 First installed industrial robot First palletizing robot Unimate Palletizer George Devol Fuji Yusoki Kogyo Timeline • Date: • Significance: • Robot Name: • Inventor:

1963 1973 First palletizing robot First robot with six electromechanically driven axes Palletizer Famulus Fuji Yusoki Kogyo KUKA Robot Group Timeline • Date: • Significance: • Robot Name: • Inventor:

1973 1975 First robot with six electromechanically driven axes Programmable universal manipulation arm, a Unimation product Famulus PUMA KUKA Robot Group Victor Scheinman Timeline • Date: • Significance: • Robot Name: • Inventor:

Laws of Robotics • Law 1: A robot may not injure a human being or through inaction, allow a human being to come to harm • Law 2: A robot must obey orders given to it by human beings, except where such orders would conflict with a higher order law • Law 3: A robot must protect its own existence as long as such protection does not conflict with a higher order law

Key Components Power Conversion Unit Sensors Actuators Controller User interface Manipulator Linkage Base

Components Body • Typically defined as a graph of links and joints: • A link is a part, a shape with physical properties. • A joint is a constraint on the spatial relations of two or more links.

Components Body (Types of joint) Respectively, a ball joint, which allows rotation around x, y, and z, a hinge joint, which allows rotation around z, and a slider joint, which allows translation along x. These are just a few examples…

Components Effectors • Component to accomplish some desired physical function • Examples: – Hands – Torch – Wheels – Legs – Trumpet

Components Actuators • Common robotic actuators utilize combinations of different electro mechanical devices – Synchronous motor – Stepper motor – AC servo motor – Brushless DC servo motor – Brushed DC servo motor

Components Actuators (Examples) Pneumatic Cylinder Hydraulic Motor DC Motor Stepper Motor Stepper Motor Servo Motor

Components Sensors • Human senses: sight, sound, touch, taste, and smell provide us vital information to function and survive • Robot sensors: measure robot configuration/condition and its environment and send such information to robot controller as electronic signals (e.g., arm position, presence of toxic gas) • Robots often need information that is beyond 5 human senses (e.g., ability to: see in the dark, detect tiny amounts of invisible radiation, measure movement that is too small or fast for the human eye to see) Accelerometer Using Piezoelectric Effect Flexiforce Sensor

Components Sensors • Vision Sensor: e.g., to pick bins, perform inspection, etc. In-Sight Vision Sensors • Part-Picking: Robot can handle In-Sight Vision Sensors work pieces that are randomly piled by using 3-D vision sensor. Since alignment operation, a special parts feeder, and an alignment pallets are not required, an automatic system can be constructed at low cost.

Example Components Sensors • Force Sensor: e.g., parts fitting and insertion, force feedback in robotic surgery • Tilt sensors: e.g., to balance a robot

Components Sensors • Imaging sensors: these create a visual representation of the world. Here, a stereo vision system creates a depth map for a Grand Challenge competitor.

Components Sensors • Proprioceptive sensors: these provide information on the robot’s internal state, e.g. the position of its joints. Shaft decoders count revolutions, allowing for configuration data and odometer.

Components Controller • Provide necessary intelligence to control the manipulator/mobile robot • Process the sensory information and compute the control commands for the actuators to carry out specified tasks Storage devices: e.g., memory to store the control program and the state of the robot system obtained from the sensors

Components Controller • There are two controller paradigms – Open-loop controllers execute robot movement without feedback. – Closed-loop controllers execute robot movement and judge progress with sensors. They can thus compensate for errors.

Components Software • Hybrid architectures are software architectures combining deliberative and reactive controllers. – An example is path-planning and PD control. • The most popular hybrid software architecture is the three-layer architecture: • – Reactive layer – low-level control, tight sensor-action loop, decisions cycles (DCs) order of milliseconds. • – Executive layer – directives from deliberative layer sequenced for reactive layer, representing sensor information, localization, mapping, DCs order of seconds. • – Deliberative layer – generates global solutions to complex tasks, path planning, model-based planning, analyze sensor data represented by executive layer, DCs order of minutes.

Uses • Agriculture • Automobile • Construction • Entertainment • Health care: hospitals, patient-care, surgery , research, etc. • Laboratories: science, engineering , etc. • Law enforcement: surveillance, patrol, etc. • Manufacturing • Military: surveillance, attack, etc. • Mining, excavation, and exploration • Transportation: air, ground, rail, space, etc. • Utilities: gas, water, and electric • Warehouses

Uses • Jobs that are dangerous for humans Decontaminating Robot Cleaning the main circulating pump housing in the nuclear power plant

Uses • Repetitive jobs that are boring, stressful, or labor-intensive for humans Welding Robot

Uses • Menial tasks that human don’t want to do Menial tasks that human don’t want to do

Uses • Robots in Space NASA Space Station

Uses • Robots in Hazardous Environments TROV in Antarctica operating under water

Uses • Medical Robots Robotic assistant for micro surgery

Thanking You...... Foysal MOHD Shawon ID: 071-163-041 Group: (D) Mob: 01913-258484 Email: [email protected] Web page: www.foysal.synthasite.com

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MIT Technology Review

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An OpenAI spinoff has built an AI model that helps robots learn tasks like humans

But can it graduate from the lab to the warehouse floor?

  • James O'Donnell archive page

In the summer of 2021, OpenAI quietly shuttered its robotics team, announcing that progress was being stifled by a lack of data necessary to train robots in how to move and reason using artificial intelligence. 

Now three of OpenAI’s early research scientists say the startup they spun off in 2017, called Covariant, has solved that problem and unveiled a system that combines the reasoning skills of large language models with the physical dexterity of an advanced robot.

The new model, called RFM-1, was trained on years of data collected from Covariant’s small fleet of item-picking robots that customers like Crate & Barrel and Bonprix use in warehouses around the world, as well as words and videos from the internet. In the coming months, the model will be released to Covariant customers. The company hopes the system will become more capable and efficient as it’s deployed in the real world. 

So what can it do? In a demonstration I attended last week, Covariant cofounders Peter Chen and Pieter Abbeel showed me how users can prompt the model using five different types of input: text, images, video, robot instructions, and measurements. 

For example, show it an image of a bin filled with sports equipment, and tell it to pick up the pack of tennis balls. The robot can then grab the item, generate an image of what the bin will look like after the tennis balls are gone, or create a video showing a bird’s-eye view of how the robot will look doing the task. 

If the model predicts it won’t be able to properly grasp the item, it might even type back, “I can’t get a good grip. Do you have any tips?” A response could advise it to use a specific number of the suction cups on its arms to give it better a grasp—eight versus six, for example. 

This represents a leap forward, Chen told me, in robots that can adapt to their environment using training data rather than the complex, task-specific code that powered the previous generation of industrial robots. It’s also a step toward worksites where managers can issue instructions in human language without concern for the limitations of human labor. (“Pack 600 meal-prep kits for red pepper pasta using the following recipe. Take no breaks!”)

Lerrel Pinto, a researcher who runs the general-purpose robotics and AI lab at New York University and has no ties to Covariant, says that even though roboticists have built basic multimodal robots before and used them in lab settings, deploying one at scale that’s able to communicate in this many modes marks an impressive feat for the company. 

To outpace its competitors, Covariant will have to get its hands on enough data for the robot to become useful in the wild, Pinto told me. Warehouse floors and loading docks are where it will be put to the test, constantly interacting with new instructions, people, objects, and environments. 

“The groups which are going to train good models are going to be the ones that have either access to already large amounts of robot data or capabilities to generate those data,” he says.

Covariant says the model has a “human-like” ability to reason, but it has its limitations. During the demonstration, in which I could see a live feed of a Covariant robot as well as a chat window to communicate with it, Chen invited me to prompt the model with anything I wanted. When I asked the robot to “return the banana to Tote Two,” it struggled with retracing its steps, leading it to pick up a sponge, then an apple, then a host of other items before it finally accomplished the banana task. 

“It doesn’t understand the new concept,” Chen said by way of explanation, “but it’s a good example—it might not work well yet in the places where you don’t have good training data.”

The company’s new model embodies a paradigm shift rippling through the robotics world. Rather than teaching a robot how the world works manually, through instructions like physics equations and code, researchers are teaching it in the same way humans learn: through millions of observations. 

The result “really can act as a very effective flexible brain to solve arbitrary robot tasks,” Chen said. 

The playing field of companies using AI to power more nimble robotic systems is likely to grow crowded this year. Earlier this month, the humanoid-robotics startup Figure AI announced it would be partnering with OpenAI and raised $675 million from tech giants like Nvidia and Microsoft. Marc Raibert, the founder of Boston Dynamics, recently started an initiative to better integrate AI into robotics.  

This means that advancements in machine learning will likely start translating to advancements in robotics. However, some issues remain unresolved. If large language models continue to be trained on millions of words without compensating the authors of those words, perhaps it will be expected that robotics models will also be trained on videos without paying their creators. And if language models hallucinate and perpetuate biases, what equivalents will surface in robotics?

In the meantime, Covariant will push forward, keen on having RFM-1 continually learn and refine. Eventually, the researchers aim to have the robot train on videos that the model itself creates—the type of meta-learning that not only makes my head spin but also sparks concern about what will happen if errors made by the model compound themselves. But with such a hunger for more training data, researchers see it almost as inevitable.

Artificial intelligence

Large language models can do jaw-dropping things. but nobody knows exactly why..

And that's a problem. Figuring it out is one of the biggest scientific puzzles of our time and a crucial step towards controlling more powerful future models.

  • Will Douglas Heaven archive page

The AI Act is done. Here’s what will (and won’t) change

The hard work starts now.

  • Melissa Heikkilä archive page

Advancing AI innovation with cutting-edge solutions  

Power your business transformation with proven AI services and infrastructure.

  • Lachlan Ainley archive page

What’s next for generative video

OpenAI's Sora has raised the bar for AI moviemaking. Here are four things to bear in mind as we wrap our heads around what's coming.

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Navigating the challenges and opportunities of synthetic voices.

We’re sharing lessons from a small scale preview of Voice Engine, a model for creating custom voices.

Tts Custom Voice Cover

OpenAI is committed to developing safe and broadly beneficial AI . Today we are sharing preliminary insights and results from a small-scale preview of a model called Voice Engine, which uses text input and a single 15-second audio sample to generate natural-sounding speech that closely resembles the original speaker. It is notable that a small model with a single 15-second sample can create emotive and realistic voices.

We first developed Voice Engine in late 2022, and have used it to power the preset voices available in the text-to-speech API as well as ChatGPT Voice and Read Aloud . At the same time, we are taking a cautious and informed approach to a broader release due to the potential for synthetic voice misuse. We hope to start a dialogue on the responsible deployment of synthetic voices, and how society can adapt to these new capabilities. Based on these conversations and the results of these small scale tests, we will make a more informed decision about whether and how to deploy this technology at scale.

Early applications of Voice Engine

To better understand the potential uses of this technology, late last year we started privately testing it with a small group of trusted partners. We've been impressed by the applications this group has developed. These small scale deployments are helping to inform our approach, safeguards, and thinking about how Voice Engine could be used for good across various industries. A few early examples include:

  • Providing reading assistance to non-readers and children through natural-sounding, emotive voices representing a wider range of speakers than what's possible with preset voices. Age of Learning , an education technology company dedicated to the academic success of children, has been using this to generate pre-scripted voice-over content. They also use Voice Engine and GPT-4 to create real-time, personalized responses to interact with students. With this technology, Age of Learning has been able to create more content for a wider audience.

1. Reference audio

2. generated audio.

  • Translating content , like videos and podcasts, so creators and businesses can reach more people around the world, fluently and in their own voices. One early adopter of this is HeyGen , an AI visual storytelling platform that works with their enterprise customers to create custom, human-like avatars for a variety of content, from product marketing to sales demos. They use Voice Engine for video translation, so they can translate a speaker's voice into multiple languages and reach a global audience. When used for translation, Voice Engine preserves the native accent of the original speaker: for example generating English with an audio sample from a French speaker would produce speech with a French accent.
  • Reaching global communities , by improving essential service delivery in remote settings. Dimagi is building tools for community health workers to provide a variety of essential services, such as counseling for breastfeeding mothers. To help these workers develop their skills, Dimagi uses Voice Engine and GPT-4 to give interactive feedback in each worker's primary language including Swahili or more informal languages like Sheng, a code-mixed language popular in Kenya.
  • Breastfeeding
  • Supporting people who are non-verbal , such as therapeutic applications for individuals with conditions that affect speech and educational enhancements for those with learning needs. Livox , an AI alternative communication app, powers Augmentative & Alternative Communication (AAC) devices that enable people with disabilities to communicate. By using Voice Engine, they are able to offer people who are non-verbal unique and non-robotic voices across many languages. Their users can choose speech that best represents them, and for multilingual users, maintain a consistent voice across each spoken language.
  • Helping patients recover their voice , for those suffering from sudden or degenerative speech conditions. The Norman Prince Neurosciences Institute at Lifespan , a not-for-profit health system that serves as the primary teaching affiliate of Brown University's medical school, is exploring uses of AI in clinical contexts. They've been piloting a program offering Voice Engine to individuals with oncologic or neurologic etiologies for speech impairment. Since Voice Engine requires such a short audio sample, doctors Fatima Mirza, Rohaid Ali and Konstantina Svokos were able to restore the voice of a young patient who lost her fluent speech due to a vascular brain tumor, using audio from a video recorded for a school project.

1. Current voice

2. reference audio, 3. generated audio, building voice engine safely.

We recognize that generating speech that resembles people's voices has serious risks, which are especially top of mind in an election year. We are engaging with U.S. and international partners from across government, media, entertainment, education, civil society and beyond to ensure we are incorporating their feedback as we build. 

The partners testing Voice Engine today have agreed to our usage policies , which prohibit the impersonation of another individual or organization without consent or legal right. In addition, our terms with these partners require explicit and informed consent from the original speaker and we don’t allow developers to build ways for individual users to create their own voices. Partners must also clearly disclose to their audience that the voices they're hearing are AI-generated. Finally, we have implemented a set of safety measures, including watermarking to trace the origin of any audio generated by Voice Engine, as well as proactive monitoring of how it's being used. 

We believe that any broad deployment of synthetic voice technology should be accompanied by voice authentication experiences that verify that the original speaker is knowingly adding their voice to the service and a no-go voice list that detects and prevents the creation of voices that are too similar to prominent figures.

Looking ahead

Voice Engine is a continuation of our commitment to understand the technical frontier and openly share what is becoming possible with AI. In line with our approach to AI safety and our voluntary commitments , we are choosing to preview but not widely release this technology at this time. We hope this preview of Voice Engine both underscores its potential and also motivates the need to bolster societal resilience against the challenges brought by ever more convincing generative models. Specifically, we encourage steps like:

  • Phasing out voice based authentication as a security measure for accessing bank accounts and other sensitive information
  • Exploring policies to protect the use of individuals' voices in AI
  • Educating the public in understanding the capabilities and limitations of AI technologies, including the possibility of deceptive AI content
  • Accelerating the development and adoption of techniques for tracking the origin of audiovisual content, so it's always clear when you're interacting with a real person or with an AI

It's important that people around the world understand where this technology is headed, whether we ultimately deploy it widely ourselves or not. We look forward to continuing to engage in conversations around the challenges and opportunities of synthetic voices with policymakers, researchers, developers and creatives.

IMAGES

  1. Anatomy of a Robot

    presentation of robots

  2. Robots Exhibition Isometric Poster 480943 Vector Art at Vecteezy

    presentation of robots

  3. Modern androids and humanoids evolution of robots Vector Image

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  4. PPT

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  5. Amazing Robot Presentation Template and Google Slides themes

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  6. Robotics PPT

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VIDEO

  1. What is ROBOTICS

  2. Introduction to Robotics (Robotics Basics)

  3. Lecture 1

  4. What is Robotics

  5. Lecture 2

  6. Lecture 01: Introduction to Robots and Robotics

COMMENTS

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  22. Navigating the Challenges and Opportunities of Synthetic Voices

    Translating content, like videos and podcasts, so creators and businesses can reach more people around the world, fluently and in their own voices.One early adopter of this is HeyGen, an AI visual storytelling platform that works with their enterprise customers to create custom, human-like avatars for a variety of content, from product marketing to sales demos.