Lidar, which stands for light detection and ranging, has been around for more than half a century. But only in recent years—thanks to self-driving cars—is it poised to become a household name. To understand why the technology is only now gaining mainstream recognition, we decided to explore lidar’s origins.
Lidar: a brief history
Lidar is a remote sensing technology that uses pulses of light to measure the distance from a sensor to a target, and generates precise, three-dimensional representations of that target. It’s similar to how whales or bats use echolocation to understand what’s in the environment around them.
Lidar’s origins date as far back as the 1930s, when researchers first attempted to measure distance by light beams to study the heights of clouds. With the advent of lasers in the 1960s came the first attempts to use lidar as a method for collecting highly detailed, local elevation data by using airplanes as platforms for lidar laser beams.
But it wasn’t until the 1980s when global positioning system (GPS) equipment—which could be used to record the location coordinates of the sensor—became commercially available that lidar gained broader adoption. Using a combination of GPS, and inertial measuring units (IMUs) to measure the angular orientation of the scanner relative to the ground, applications for lidar began advancing in more meaningful ways.
Aerial applications for lidar
Lidar processes its data (e.g., the coordinates from returning laser pulses it collects) as a 3D visualization called a point cloud that is an incredibly detailed representation of the environment and surrounding objects. This data provides insights that we wouldn’t otherwise be able to glean from different sensors.
Since the late 1980s, people have primarily mounted lidar systems to airplanes, unmanned aerial vehicles (UAVs), and helicopters with the goal of surveying broad swaths of land. A few examples of industries that use lidar data from aerial platforms include:
- Forestry, to study the height and health of trees
- Agriculture, to help farmers make decisions about where to apply precious resources such as fertilizer and water
- Environmental sciences, including scientists at the National Oceanic and Atmospheric Administration (NOAA) who use lidar to produce more accurate shoreline maps, make digital elevation models for use in geographic information systems, and assist in emergency response operations
- The military, to create detailed maps of potential targets
- Archeology, to create elevation maps of sites that can show archeologists micro-topography that might otherwise be hidden by vegetation
Ground applications for lidar
There are several use cases for ground-based lidar systems as well. Perhaps the most well-known today is for self-driving cars. In addition to vehicles, other ground-based lidar systems are mounted to tripods or other structures. Here’s a small sampling of applications for ground-based lidar:
- Autonomous vehicles, to map a vehicle’s surroundings and objects in its path
- Construction, to conduct internal building mapping for floor plans
- Geology, to perform outcrop mapping and deformation monitoring
- Forestry, to conduct forest inventory to glean information about biomass, stem volume, biodiversity, and more
- Heritage preservation, to capture imagery and data from cultural sites that help in preservation and restoration efforts
What’s next for lidar?
If autonomous vehicles are the rising tide lifting lidar into our mainstream vocabulary, they’re also very likely to be key drivers (pun intended) of change for the technology, most notably for opening up access to sensors. Lidar is expensive, making it cost-prohibitive for some companies to get their hands on more sophisticated models. For example, Velodyne’s 64-laser lidar retails for $75,000, too steep a price to mount one on every autonomous vehicle. But that’s changing.
As demand for the technology grows in the booming autonomous vehicle industry, experts predict companies will innovate to substantially lower the price of sensors, particularly with the advent of solid-state lidar. Solid-state lidar does not rely on spinning parts like many of the more expensive units do, making it more compact and less expensive. This article from Ars Technica provides a detailed and comprehensive view of why lidar sensors will likely be drastically less expensive in the near future.
Another way the technology is likely to change—thanks to lidar’s place as a central component to many autonomous vehicle perception programs—is in improved resolution. With high demand for lidar has come a surge of startups looking to enter the space. In the coming years, expect to see systems with higher quality outputs and stronger capabilities in object recognition and tracking.
Editor’s Note: Interested in learning more about lidar? Check out this summary of the top open-source lidar driving datasets available today.
image credit: Aaron Parecki