How Robots Work

Most robots have movable bodies. Some only have motorized wheels, and others have dozens of movable segments, typically made of metal or plastic. Like the bones in your body, the individual segments are connected together with joints.

Robots spin wheels and pivot jointed segments with some sort of actuator. Some robots use electric motors and solenoids as actuators; some use a hydraulic system; and some use a pneumatic system (a system driven by compressed gases). Robots may use a combination of all these actuator types.

A robot needs a power source to drive these actuators. Most robots either have batteries or plug into the wall. Some may use solar power or fuel cells. Hydraulic robots also need a pump to pressurize the hydraulic fluid, and pneumatic robots need an air compressor or compressed-air tanks.

The actuators are all wired to electrical circuits. The circuits power electrical motors and solenoids directly and activate hydraulic systems by manipulating electrical valves. The valves determine the pressurized fluid's path through the machine. To move a hydraulic leg, for example, the robot's controller would open the valve leading from the fluid pump to a piston cylinder attached to that leg. The pressurized fluid would extend the piston, swiveling the leg forward. Typically, in order to move their segments in two directions, robots use pistons that can push both ways.

The robot's computer controls everything attached to the circuits. To move the robot, the computer switches on all the necessary motors and valves. Many robots are reprogrammable — to change the robot's behavior, you update or change the software that gives the robot its instructions.

Not all robots have sensory systems, and few can see, hear, smell or taste. The most common robotic sense is the sense of movement — the robot's ability to monitor its own motion. One way to do this is to use a laser on the bottom of the robot to illuminate the floor while a camera measures the distance and speed traveled. This is the same basic system used in computer mice. Roomba vacuums use infrared light to detect objects in their path and photoelectric cells measure changes in light.

These are the basic nuts and bolts of robotics. Roboticists can combine these elements in an infinite number of ways to create robots of unlimited complexity.

The term robot comes from the Czech word robota, generally translated as "forced labor." This describes the majority of robots fairly well. Most robots in the world are designed for heavy, repetitive manufacturing work. They handle tasks that are difficult, dangerous or boring to human beings.

For example, the robotic arm is frequently used in manufacturing roles. A typical robotic arm is made up of seven metal segments, joined by six joints. The computer controls the robot by rotating individual stepper motors connected to each joint (some larger arms use hydraulics or pneumatics). Unlike ordinary motors, step motors move in exact increments. This allows the computer to move the arm very precisely, performing the same movement over and over. The robot uses motion sensors to make sure it moves just the right amount.

An industrial robot with six joints closely resembles a human arm — it has the equivalent of a shoulder, an elbow and a wrist. Typically, the shoulder is mounted to a stationary base structure rather than to a movable body. This type of robot has six degrees of freedom, meaning it can pivot in six different ways. A human arm, by comparison, has seven degrees of freedom.

Your arm's job is to move your hand from place to place. Similarly, the robotic arm's job is to move an end effector from place to place. You can outfit robotic arms with all sorts of end effectors, which are suited to a particular application. One common end effector is a simplified version of the hand, which can grasp and carry different objects. Robotic hands often have built-in pressure sensors that tell the computer how hard the robot is gripping a particular object. This keeps the robot from dropping or breaking whatever it's carrying. Other end effectors include blowtorches, drills and spray painters.

Industrial robots are designed to do the same thing. For example, a robot might twist the caps onto peanut butter jars coming down an assembly line. To teach a robot how to do its job, the programmer guides the arm through the motions using a handheld controller. The robot stores the exact sequence of movements in its memory and does it again every time a new unit comes down the assembly line.

Most industrial robots work in auto assembly lines, putting cars together. Robots can do a lot of this work more efficiently than human beings because they are so precise. They always drill in the same place, and they always tighten bolts with the same amount of force, no matter how many hours they've been working. Manufacturing robots are also very important in the computer industry. It takes an incredibly precise hand to put together a tiny microchip.

You may find robots working alongside construction workers, plastering walls accurately and faster than a human can do the job. Robots assist in underwater exploration. Surgeons use robots to handle delicate surgeries. They even handle flipping burgers in the kitchen. These robots all have a form of robotic arm.

Robotic arms are important in space exploration. NASA uses an arm with seven degrees of freedom — like our own arms — to capture equipment for servicing or to grab asteroids. The 7-foot (2-meter) robotic arm on the Perseverance rover has several special tools it uses as it explores the surface of Mars. A camera helps scientists see what's going on to guide the arm. There's also an abrading tool used to grind rock samples and a coring drill can collect samples to store in metal tubes that it drops on the surface for return to Earth on future missions. An X-ray device called PIXL (short for Planetary Instrument for X-ray Lithochemistry) has a hexapod with six little mechanical legs that it uses to adjust the X-ray for the best angle.

The Scanning Habitable Environments with Raman and Luminescence for Organics & Chemicals (aka SHERLOC) identifies minerals by the way light scatters from them. The Wide Angle Topographic Sensor for Operations and eNgineering (aka — you guessed it — WATSON) then takes close-up photos for the Earth-bound scientists. They use the two devices to create a mineral map of the red planet's surface.

Robotic arms are relatively easy to build and program because they only operate within a confined area. Things get a bit trickier when you send a robot out into the world.

First, the robot needs a working locomotion system. If the robot only needs to move over smooth ground, wheels are often the best option. Wheels and tracks can also work on rougher terrain. But robot designers often look to legs instead, because they are more adaptable. Building legged robots also helps researchers understand natural locomotion — it's a useful exercise in biological research.

Typically, hydraulic or pneumatic pistons move robot legs. The pistons attach to different leg segments just like muscles attach to different bones. It's a real trick getting all these pistons to work together properly. As a baby, your brain had to figure out exactly the right combination of muscle contractions to walk upright without falling over. Similarly, a robot designer has to figure out the right combination of piston movements involved in walking and program this information into the robot's computer. Many mobile robots have a built-in balance system (a collection of gyroscopes, for example) that tells the computer when it needs to correct its movements.

Designers commonly look to the animal world for robotic locomotion ideas. Six-legged insects have exceptionally good balance, and they adapt well to a wide variety of terrain. Four-legged robots such as Boston Dynamics' Spot look like dogs, and the similarity breeds comparisons as they take on dangerous jobs such as construction inspection. Two-legged robots are challenging to balance properly, but humans have gotten better with practice. Boston Dynamics' Atlas can even do parkour.

Aerial robots are also inspired by real-world examples. Although many use wings like we see on airplanes, researchers have also developed techniques using fly-wing-like soft actuators. Most people now are familiar with the propeller-powered drones that provide amazing camera shots for entertainment, sporting events and surveillance. Some of these hovering bots can also be networked together to create swarms of robots such as those seen at the Tokyo Summer Olympic Games in 2021.

Underwater, robots may walk across the sea floor. One example is Silver 2, a crab-like robot designed to find and clean up plastic waste. The Benthic Rover II uses treads instead. Snake robots, which of course take their name from the animals whose locomotion they copy, can operate underwater and on land. They even work well in the human body, where they can perform surgical repairs.

Some mobile robots are controlled by remote — a human tells them what to do and when to do it. The remote control might communicate with the robot through an attached wire, or using radio or infrared signals. Remote robots are useful for exploring dangerous or inaccessible environments, such as the deep sea or inside a volcano. Some robots are only partially controlled by remote. For example, the operator might direct the robot to go to a certain spot, but instead of steering it there, the robot finds its own way.

Autonomous robots act on their own. Humans program the robot to respond to outside stimuli. The very simple bump-and-go robot is a good illustration of how this works.

This sort of robot has a bumper sensor to detect obstacles. When you turn the robot on, it zips along in a straight line. When it finally hits an obstacle, the impact triggers its bumper sensor. The robot's programming tells it to back up, turn to the right and move forward again, in response to every bump. In this way, the robot changes direction any time it encounters an obstacle.

Some autonomous robots can only work in a familiar, constrained environment. Lawn-mowing robots, for example, depend on buried border markers to define the limits of their yard. An office-cleaning robot might need a map of the building in order to maneuver from point to point. Amazon's warehouse robots use colored magnetic tape on the warehouse floor to help them navigate. Among other jobs, the online retailer uses bots to deliver items to humans, keeping their employees focused on packaging orders rather than searching warehouse shelves.

Mobile robots often use infrared or ultrasound sensors to see obstacles. These sensors work the same way as animal echolocation: The robot sends out a sound signal or a beam of infrared light and detects the signal's reflection. The robot locates the distance to obstacles based on how long it takes the signal to bounce back. More sophisticated robots may be equipped with Light Detection and Ranging (lidar) equipment, which uses light rather than sound to help the robot determine its position within its environment.

Even off-the-shelf robotic vacuums use several methods to find their way around your living room. In addition to bump sensors, they have cliff sensors (is it about to fall?), wall sensors (what's ahead of it?) and optical encoders (how far has it gone?). Creating a map using multiple sensors this way is known as simultaneous localization and mapping (SLAM).

Some robots use stereo vision to see the world around them. Two cameras give these robots depth perception, and image-recognition software gives them the ability to locate and classify various objects. Robots might also use microphones and smell sensors to analyze the world around them. Boston Dynamics' Spot dog-like robot is equipped with a 360-degree panoramic camera, but the company also offers pan-tilt-zoom and infrared radiometric cameras. This enabled the U.S. Marines to test the robot's ability to look around corners to find enemies before venturing out into the open.

More advanced robots analyze and adapt to unfamiliar environments, even to areas with rough terrain. These robots may associate certain terrain patterns with certain actions. A rover robot, for example, might construct a map of the land in front of it based on its visual sensors. If the map shows a very bumpy terrain pattern, the robot knows to travel another way. NASA's Perseverance rover is an example.

Follower robots learn from watching us. Autonomous farming robot manufacturer Burro uses a combination of cameras and GPS to get around, but the robot's artificial intelligence system learns its job by following humans around. Piaggio Fast Forward's Gita robots follow their human leaders while carrying their stuff. The device can even tail you while you're on your bike. It has a maximum speed of 35 miles per hour (56 kilometers per hour).

In the last couple of sections, we looked at the most prominent fields in the world of robots — industry robotics and research robotics. Professionals in these fields have made most of the major advancements in robotics over the years, but they aren't the only ones making robots. For decades, a small but passionate band of hobbyists has been creating robots in garages and basements all over the world.

Homebrew robotics is a rapidly expanding subculture with a sizable web presence. Amateur roboticists may cobble together their creations using whatever is on hand, such as old toys, VCRs and other random leftover gadgets, but the maker movement has made it easy to find components, share ideas and educate others about DIY electronics.

Robots are only part of the maker movement, but many DIY tools can be used for a wide range of applications. Inexpensive single-board computers are powerful enough for more elaborate projects. Sites like Instructables and Thingiverse let makers share plans with one another. There are makerspaces, hackerspaces and fablabs inside schools, universities, libraries and even in communities for people to borrow tools and learn from one another as they put together their own creations. Many have 3-D printers available to print robot parts to your custom specifications.

Home-made robots are as varied as professional robots. Some weekend roboticists tinker with elaborate walking machines, some design their own service bots and others create competitive robots. The most familiar competitive robots are remote control fighters like you might see on "BattleBots." Some may not consider BattleBots to be "true robots" because they don't have reprogrammable computer brains. They're basically souped-up remote control cars.

More advanced competitive robots are controlled by computer. Soccer robots, for example, play soccer with no human input at all. A standard soccer bot team includes several individual robots that communicate with a central computer. The computer "sees" the entire soccer field with a video camera and identifies its own team members, its opponent's members, the ball and the goal based on their color. The computer uses this information to decide how to direct its team.

Artificial intelligence (AI) is arguably the most exciting field in robotics. It's certainly the most controversial: Everybody agrees that a robot can work in an assembly line, but there's no consensus on whether a robot can ever be intelligent.

Like the term "robot" itself, artificial intelligence is hard to define. Ultimate AI would be a recreation of the human thought process — a human-made machine with our intellectual abilities. This would include the ability to learn just about anything, the ability to reason, the ability to use language and the ability to formulate original ideas. Roboticists are nowhere near achieving this level of artificial intelligence, but they have made a lot of progress with more limited AI. Today's AI machines can replicate some specific elements of intellectual ability.

Computers can already solve problems in limited realms. The basic idea of AI problem-solving is simple, though its execution is complicated. First, the AI robot or computer gathers facts about a situation through sensors or human input. The computer compares this information to stored data and decides what the information signifies. The computer runs through various possible actions and predicts which action will be most successful based on the collected information. For the most part, the computer can only solve problems it's programmed to solve — it doesn't have any generalized analytical ability. Chess computers are one example of this sort of machine.

Some modern robots also can learn in a limited capacity. Learning robots recognize if a certain action (moving its legs in a certain way, for instance) achieves a desired result (navigating an obstacle). The robot stores this information and attempts the successful action the next time it encounters the same situation. Robotic vacuums learn the layout of a room, but they're built for vacuuming and nothing else.

Some robots can interact socially. Kismet, a robot created in 1998 at M.I.T.'s Computer Science & Artificial Intelligence Lab (CSAIL), recognized human body language and voice inflection and responded appropriately. Since then, interactive robots have become available commercially, and some are being used as companions for senior citizens. Although the robots are helpful for cleaning and mobility assistance, adding interactivity helps reduce seniors' social isolation.

The real challenge of AI is to understand how natural intelligence works. Developing AI isn't like building an artificial heart — scientists don't have a simple, concrete model to work from. We do know that the brain contains billions and billions of neurons, and that we think and learn by establishing electrical connections between different neurons. But we don't know exactly how all of these connections add up to higher reasoning, or even low-level operations. The complex circuitry seems incomprehensible.

Because of this, AI research is largely theoretical. Scientists hypothesize on how and why we learn and think, and they experiment with their ideas using robots. M.I.T. CSAIL researchers focus on humanoid robots because they feel that being able to experience the world like a human is essential to developing human-like intelligence. It also makes it easier for people to interact with the robots, which potentially makes it easier for the robot to learn.

Just as physical robotic design is a handy tool for understanding animal and human anatomy, AI research is useful for understanding how natural intelligence works. For some roboticists, this insight is the ultimate goal of designing robots. Others envision a world where we live side by side with intelligent machines and use a variety of lesser robots for manual labor, health care and communication. Some robotics experts predict that robotic evolution will ultimately turn us into cyborgs — humans integrated with machines. Conceivably, people in the future could load their minds into a sturdy robot and live for thousands of years!

In any case, robots will certainly play a larger role in our daily lives in the future. In the coming decades, robots will gradually move out of the industrial and scientific worlds and into daily life, in the same way that computers spread to the home in the 1980s.