The eyes of a self-driving car are called LIDAR sensors.
LIDAR is a portmanteau of “light” and “radar.” In essence, these sensors monitor their surroundings by shining a light on an object and measuring the time needed for it to bounce back. They work well enough, but they aren’t without their drawbacks. Today’s self-driving cars typically use LIDARs that are quite large and expensive. Google, for instance, used $80,000 LIDARs with its early designs. “Most vehicles in the DARPA urban challenge put half-a-million-dollars worth of sensors on the car,” says Daniela Rus, the director of MIT’s Computer Science and Artificial Intelligence Laboratory, referring to the government-backed competition that helped spawn Google’s autonomous vehicles.
But researchers at the University of California, Berkeley say they’ve developed a new breed of laser technology that could significantly reduce the size, weight, cost, and power consumption of LIDARs, potentially leading to a much broader range of autonomous vehicles. “This is important for unmanned vehicles on land and in the sky,” says Weijian Yang, one of the researchers behind the project.
Yang’s work is part of a wider effort to refine LIDARs and build a cheaper breed of autonomous cars and other vehicles. A German company called SICK already offers a LIDAR that sells for less than $10,000, and researchers from MIT and the National Research Foundation of Singapore, including Rus, recently built a self-driving golf cart using no more than four of these units (see video below). As LIDAR technology improves—and as we improve the algorithms that process the data gathered from these sensors—we’ll bring autonomy not just to cars but smaller contraptions, including golf carts, robots, and flying drones.
Anatomy of a LIDAR
A LIDAR operates by repeatedly changing the wavelength of a laser, so that the sensor can properly identify the light as it bounces off an object and returns to the sensor, and such wavelength changes require the precise manipulation of a mirror—or sometimes multiple mirrors. Typically, a separate electrical device moves these mirrors to and fro. But at Berkeley, Yang and his team developed a new option. They can move the mirrors with the laser itself.
“You don’t need an external electrical source,” says Yang, the lead author on the paper describing the technology, which was published today in the journal Scientific Reports. “The laser can change the position of the mirror automatically. The light has some kind of force.”
The result: they don’t need that outside electrical device, the sensor is smaller and lighter, and it consumes less power. The laser can be integrated with the mirror. The whole device can squeeze into a few hundred square micrometers of space. And it can be powered with the equivalent AA battery.
A More Accurate Picture
According to Yang, this same technology could improve optical coherence tomography, or OCT, which is used in medical imaging equipment. But the most intriguing possibilities lie in the world of robotics. Among other things, Yang explains, Berkeley’s method allows lasers to change wavelengths more frequently—one microsecond versus 10 or so milliseconds—and that means a LIDAR could potentially take more readings, more quickly. In other words, it could provide a more accurate picture of its surroundings.
Emilio Frazzoli, an MIT researcher who worked alongside Rus on those self-driving golf carts, says that smaller, cheaper LIDARs aren’t essential to the near future of self-driving cars. “Right now, these sensors are still expensive, but they’re becoming better and cheaper, and I don’t see them as a bottleneck,” he says, pointing out that even with today’s sensors, the price of a self-driving car compares favorably to how much you’d speed for a standard car and a full-time driver. But he says that better sensors are certainly welcome, particularly for other applications. Indeed, Yang believes that his work could help drive the creation of additional autonomous vehicles and robots, including contraptions the size of a smartphone. In the years to come, more machines will have eyes than you might expect.