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 History 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.

Robo-cabulary Human-robot interaction A field of robotics that studies the relationship between people and machines. For example, a self-driving car could see a stop sign and hit the brakes at the last minute, but that would terrify pedestrians and passengers alike. By studying human-robot interaction, roboticists can shape a world in which people and machines get along without hurting each other. Humanoid The classical sci-fi robot. This is perhaps the most challenging form of robot to engineer, on account of it being both technically difficult and energetically costly to walk and balance on two legs. But humanoids may hold promise in rescue operations, where they’d be able to better navigate an environment designed for humans, like a nuclear reactor. Actuator Typically, a combination of an electric motor and a gearbox. Actuators are what power most robots. Soft robotics A field of robotics that foregoes traditional materials and motors in favor of generally softer materials and pumping air or oil to move its parts. Lidar Lidar, or light detection and ranging, is a system that blasts a robot’s surroundings with lasers to build a 3-D map. This is pivotal both for self-driving cars and for service robots that need to work with humans without running them down. Singularity The hypothetical point where the machines grow so advanced that humans are forced into a societal and existential crisis. Multiplicity The idea that robots and AI won’t supplant humans, but complement them.

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.

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.